Year |
Citation |
Score |
2020 |
Nazábal A, Olmos PM, Ghahramani Z, Valera I. Handling incomplete heterogeneous data using VAEs Pattern Recognition. 107: 107501. DOI: 10.1016/j.patcog.2020.107501 |
0.349 |
|
2019 |
Lomelí M, Rowland M, Gretton A, Ghahramani Z. Antithetic and Monte Carlo kernel estimators for partial rankings Statistics and Computing. 29: 1127-1147. DOI: 10.1007/s11222-019-09859-z |
0.351 |
|
2016 |
Hernández-Lobato JM, Gelbart MA, Adams RP, Hoffman MW, Ghahramani Z. A general framework for constrained Bayesian optimization using information-based search Journal of Machine Learning Research. 17: 5549-5601. DOI: 10.17863/Cam.6477 |
0.532 |
|
2015 |
Palla K, Knowles DA, Ghahramani Z. Relational Learning and Network Modelling Using Infinite Latent Attribute Models. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 462-74. PMID 26353254 DOI: 10.1109/Tpami.2014.2324586 |
0.657 |
|
2015 |
Knowles DA, Ghahramani Z. Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 271-89. PMID 26353241 DOI: 10.1109/Tpami.2014.2313115 |
0.64 |
|
2015 |
Bousmalis K, Zafeiriou S, Morency LP, Pantic M, Ghahramani Z. Variational Infinite Hidden Conditional Random Fields. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1917-29. PMID 26353136 DOI: 10.1109/Tpami.2014.2388228 |
0.37 |
|
2015 |
Bratieres S, Quadrianto N, Ghahramani Z. GPstruct: Bayesian Structured Prediction Using Gaussian Processes. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1514-20. PMID 26352456 DOI: 10.1109/TPAMI.2014.2366151 |
0.342 |
|
2015 |
Ghahramani Z. Probabilistic machine learning and artificial intelligence Nature. 521: 452-459. PMID 26017444 DOI: 10.1038/nature14541 |
0.373 |
|
2015 |
Tarran B, Ghahramani Z. How machines learned to think statistically Significance. 12: 8-15. DOI: 10.1111/j.1740-9713.2015.00796.x |
0.317 |
|
2015 |
Palla K, Knowles DA, Ghahramani Z. Relational learning and network modelling using infinite latent attribute models Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 462-474. DOI: 10.1109/TPAMI.2014.2324586 |
0.638 |
|
2015 |
Knowles DA, Ghahramani Z. Pitman yor diffusion trees for bayesian hierarchical clustering Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 271-289. DOI: 10.1109/TPAMI.2014.2313115 |
0.539 |
|
2015 |
Gal Y, Chen Y, Ghahramani Z. Latent Gaussian processes for distribution estimation of multivariate categorical data 32nd International Conference On Machine Learning, Icml 2015. 1: 645-654. |
0.305 |
|
2015 |
Ge H, Chen Y, Wan M, Ghahramani Z. Distributed inference for Dirichlet process mixture models 32nd International Conference On Machine Learning, Icml 2015. 3: 2266-2274. |
0.312 |
|
2014 |
Duvenaud D, Rippel O, Adams RP, Ghahramani Z. Avoiding pathologies in very deep networks Journal of Machine Learning Research. 33: 202-210. |
0.442 |
|
2013 |
Darkins R, Cooke EJ, Ghahramani Z, Kirk PD, Wild DL, Savage RS. Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm. Plos One. 8: e59795. PMID 23565168 DOI: 10.1371/Journal.Pone.0059795 |
0.316 |
|
2013 |
Eaton F, Ghahramani Z. Model reductions for inference: generality of pairwise, binary, and planar factor graphs. Neural Computation. 25: 1213-60. PMID 23547951 DOI: 10.1162/NECO_a_00441 |
0.331 |
|
2013 |
Ghahramani Z. Bayesian non-parametrics and the probabilistic approach to modelling. Philosophical Transactions. Series a, Mathematical, Physical, and Engineering Sciences. 371: 20110553. PMID 23277609 DOI: 10.1098/rsta.2011.0553 |
0.418 |
|
2012 |
Kirk P, Griffin JE, Savage RS, Ghahramani Z, Wild DL. Bayesian correlated clustering to integrate multiple datasets. Bioinformatics (Oxford, England). 28: 3290-7. PMID 23047558 DOI: 10.1093/Bioinformatics/Bts595 |
0.35 |
|
2011 |
Knowles D, Ghahramani Z. Nonparametric Bayesian sparse factor models with application to gene expression modeling Annals of Applied Statistics. 5: 1534-1552. DOI: 10.1214/10-Aoas435 |
0.64 |
|
2011 |
Abbott JT, Heller KA, Ghahramani Z, Griffiths TL. Testing a Bayesian measure of representativeness using a large image database Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
0.392 |
|
2011 |
Lacoste-Julien S, Huszár F, Ghahramani Z. Approximate inference for the loss-calibrated Bayesian Journal of Machine Learning Research. 15: 416-424. |
0.713 |
|
2011 |
Griffiths TL, Ghahramani Z. The Indian buffet process: An introduction and review Journal of Machine Learning Research. 12: 1185-1224. |
0.377 |
|
2010 |
Adams RP, Ghahramani Z, Jordan MI. Tree-structured stick breaking for hierarchical data Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.571 |
|
2010 |
Adams RP, Wallach HM, Ghahramani Z. Learning the structure of deep sparse graphical models Journal of Machine Learning Research. 9: 1-8. |
0.556 |
|
2009 |
Rasmussen CE, de la Cruz BJ, Ghahramani Z, Wild DL. Modeling and visualizing uncertainty in gene expression clusters using dirichlet process mixtures. Ieee/Acm Transactions On Computational Biology and Bioinformatics / Ieee, Acm. 6: 615-28. PMID 19875860 DOI: 10.1109/Tcbb.2007.70269 |
0.7 |
|
2009 |
Savage RS, Heller K, Xu Y, Ghahramani Z, Truman WM, Grant M, Denby KJ, Wild DL. R/BHC: fast Bayesian hierarchical clustering for microarray data. Bmc Bioinformatics. 10: 242. PMID 19660130 DOI: 10.1186/1471-2105-10-242 |
0.311 |
|
2009 |
Adams RP, Ghahramani Z. Archipelago: Nonparametric Bayesian semi-supervised learning Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 1-8. DOI: 10.1145/1553374.1553375 |
0.522 |
|
2009 |
Van Gael J, Teh YW, Ghahramani Z. The infinite factorial hidden Markov model Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1697-1704. |
0.605 |
|
2009 |
Adams RP, Ghahramani Z. Archipelago: Nonparametric Bayesian semi-supervised learning Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 1-8. |
0.522 |
|
2008 |
Sung J, Ghahramani Z, Bang SY. Latent-space variational bayes. Ieee Transactions On Pattern Analysis and Machine Intelligence. 30: 2236-42. PMID 18988955 DOI: 10.1109/TPAMI.2008.157 |
0.386 |
|
2008 |
Sung J, Ghahramani Z, Bang SY. Second-order latent-space variational bayes for approximate bayesian inference Ieee Signal Processing Letters. 15: 918-921. DOI: 10.1109/LSP.2008.2001557 |
0.354 |
|
2008 |
Zhang J, Ghahramani Z, Yang Y. Flexible latent variable models for multi-task learning Machine Learning. 73: 221-242. DOI: 10.1007/S10994-008-5050-1 |
0.385 |
|
2008 |
Van Gael J, Saatci Y, Teh YW, Ghahramani Z. Beam sampling for the infinite hidden Markov model Proceedings of the 25th International Conference On Machine Learning. 1088-1095. |
0.535 |
|
2007 |
Teh YW, Görür D, Ghahramani Z. Stick-breaking construction for the Indian buffet process Journal of Machine Learning Research. 2: 556-563. |
0.503 |
|
2007 |
Knowles D, Ghahramani Z. Infinite sparse factor analysis and infinite independent components analysis Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4666: 381-388. |
0.543 |
|
2007 |
Meeds E, Ghahramani Z, Neal R, Roweis S. Modeling dyadic data with binary latent factors Advances in Neural Information Processing Systems. 977-984. |
0.752 |
|
2006 |
Kim HC, Ghahramani Z. Bayesian Gaussian process classification with the EM-EP algorithm. Ieee Transactions On Pattern Analysis and Machine Intelligence. 28: 1948-59. PMID 17108369 DOI: 10.1109/TPAMI.2006.238 |
0.346 |
|
2006 |
Chu W, Ghahramani Z, Podtelezhnikov A, Wild DL. Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction. Ieee/Acm Transactions On Computational Biology and Bioinformatics / Ieee, Acm. 3: 98-113. PMID 17048397 DOI: 10.1109/TCBB.2006.17 |
0.349 |
|
2006 |
Beal MJ, Ghahramani Z. Variational Bayesian learning of directed graphical models with hidden variables Bayesian Analysis. 1: 793-832. DOI: 10.1214/06-BA126 |
0.441 |
|
2006 |
Wood F, Griffiths TL, Ghahramani Z. A non-parametric Bayesian method for inferring hidden causes Proceedings of the 22nd Conference On Uncertainty in Artificial Intelligence, Uai 2006. 536-543. |
0.425 |
|
2005 |
Penny W, Ghahramani Z, Friston K. Bilinear dynamical systems. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 360: 983-93. PMID 16087442 DOI: 10.1098/Rstb.2005.1642 |
0.345 |
|
2005 |
Beal MJ, Falciani F, Ghahramani Z, Rangel C, Wild DL. A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinformatics (Oxford, England). 21: 349-56. PMID 15353451 DOI: 10.1093/bioinformatics/bti014 |
0.37 |
|
2005 |
Griffiths TL, Ghahramani Z. Infinite latent feature models and the Indian buffet process Advances in Neural Information Processing Systems. 475-482. |
0.47 |
|
2004 |
Todorov E, Ghahramani Z. Analysis of the synergies underlying complex hand manipulation. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 6: 4637-40. PMID 17271341 DOI: 10.1109/IEMBS.2004.1404285 |
0.504 |
|
2004 |
Dubey A, Hwang S, Rangel C, Rasmussen CE, Ghahramani Z, Wild DL. Clustering protein sequence and structure space with infinite Gaussian mixture models. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 399-410. PMID 14992520 DOI: 10.1142/9789812704856_0038 |
0.678 |
|
2004 |
Rangel C, Angus J, Ghahramani Z, Lioumi M, Sotheran E, Gaiba A, Wild DL, Falciani F. Modeling T-cell activation using gene expression profiling and state-space models. Bioinformatics (Oxford, England). 20: 1361-72. PMID 14962938 DOI: 10.1093/Bioinformatics/Bth093 |
0.319 |
|
2004 |
Thrun S, Liu Y, Koller D, Ng AY, Ghahramani Z, Durrant-Whyte H. Simultaneous localization and mapping with sparse extended information filters International Journal of Robotics Research. 23: 693-716. DOI: 10.1177/0278364904045479 |
0.523 |
|
2004 |
Thrun S, Koller D, Ghahramani Z, Durrant-Whyte H, Ng AY. Simultaneous mapping and localization with sparse extended information filters: Theory and initial results Springer Tracts in Advanced Robotics. 7: 363-380. DOI: 10.1007/978-3-540-45058-0_22 |
0.441 |
|
2003 |
Todorov E, Ghahramani Z. Unsupervised Learning of Sensory-Motor Primitives Annual International Conference of the Ieee Engineering in Medicine and Biology - Proceedings. 2: 1750-1753. |
0.537 |
|
2003 |
Salakhutdinov R, Roweis S, Ghahramani Z. Optimization with EM and Expectation-Conjugate-Gradient Proceedings, Twentieth International Conference On Machine Learning. 2: 672-679. |
0.718 |
|
2002 |
Ueda N, Ghahramani Z. Bayesian model search for mixture models based on optimizing variational bounds. Neural Networks : the Official Journal of the International Neural Network Society. 15: 1223-41. PMID 12425440 DOI: 10.1016/S0893-6080(02)00040-0 |
0.409 |
|
2002 |
Raval A, Ghahramani Z, Wild DL. A Bayesian network model for protein fold and remote homologue recognition. Bioinformatics (Oxford, England). 18: 788-801. PMID 12075014 DOI: 10.1093/Bioinformatics/18.6.788 |
0.337 |
|
2002 |
Beal MJ, Ghahramani Z, Rasmussen CE. The infinite hidden markov model Advances in Neural Information Processing Systems. |
0.709 |
|
2001 |
Wolpert DM, Ghahramani Z, Flanagan JR. Perspectives and problems in motor learning. Trends in Cognitive Sciences. 5: 487-494. PMID 11684481 DOI: 10.1016/S1364-6613(00)01773-3 |
0.553 |
|
2001 |
Ghahramani Z. An introduction to hidden Markov models and Bayesian networks International Journal of Pattern Recognition and Artificial Intelligence. 15: 9-42. DOI: 10.1142/S0218001401000836 |
0.424 |
|
2000 |
Wolpert DM, Ghahramani Z. Computational principles of movement neuroscience. Nature Neuroscience. 3: 1212-7. PMID 11127840 DOI: 10.1038/81497 |
0.54 |
|
2000 |
Ueda N, Nakano R, Ghahramani Z, Hinton GE. SMEM algorithm for mixture models. Neural Computation. 12: 2109-28. PMID 10976141 |
0.665 |
|
2000 |
Ghahramani Z, Hinton GE. Variational learning for switching state-space models. Neural Computation. 12: 831-64. PMID 10770834 DOI: 10.1162/089976600300015619 |
0.722 |
|
2000 |
Ueda N, Nakano R, Ghahramani Z, Hinton GE. Split and merge EM algorithm for improving Gaussian mixture density estimates Journal of Vlsi Signal Processing Systems For Signal, Image, and Video Technology. 26: 133-140. |
0.621 |
|
2000 |
Hinton GE, Ghahramani Z, Teh YW. Learning to parse images Advances in Neural Information Processing Systems. 463-469. |
0.719 |
|
1999 |
Roweis S, Ghahramani Z. A unifying review of linear gaussian models. Neural Computation. 11: 305-45. PMID 9950734 DOI: 10.1162/089976699300016674 |
0.791 |
|
1999 |
Jordan MI, Ghahramani Z, Jaakkola TS, Saul LK. Introduction to variational methods for graphical models Machine Learning. 37: 183-233. DOI: 10.1023/A:1007665907178 |
0.781 |
|
1999 |
Ghahramani Z, Roweis ST. Learning nonlinear dynamical systems using an EM algorithm Advances in Neural Information Processing Systems. 431-437. |
0.741 |
|
1998 |
Ghahramani Z, Hinton GE. Hierarchical non-linear factor analysis and topographic maps Advances in Neural Information Processing Systems. 486-492. |
0.614 |
|
1997 |
Hinton GE, Ghahramani Z. Generative models for discovering sparse distributed representations. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 352: 1177-90. PMID 9304685 DOI: 10.1098/rstb.1997.0101 |
0.715 |
|
1997 |
Ghahramani Z, Wolpert DM. Modular decomposition in visuomotor learning. Nature. 386: 392-5. PMID 9121554 DOI: 10.1038/386392a0 |
0.574 |
|
1997 |
Ghahramani Z, Wolpert DM, Michale I. J. Computational models of sensorimotor integration Advances in Psychology. 119: 117-147. DOI: 10.1016/S0166-4115(97)80006-4 |
0.559 |
|
1997 |
Ghahramani Z, Jordan MI. Factorial Hidden Markov Models Machine Learning. 29: 245-273. |
0.5 |
|
1996 |
Ghahramani Z, Wolpert DM, Jordan MI. Generalization to local remappings of the visuomotor coordinate transformation. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 16: 7085-96. PMID 8824344 DOI: 10.1523/Jneurosci.16-21-07085.1996 |
0.61 |
|
1996 |
Cohn DA, Ghahramani Z, Jordan MI. Active learning with statistical models Journal of Artificial Intelligence Research. 4: 129-145. DOI: 10.1613/Jair.295 |
0.55 |
|
1995 |
Wolpert DM, Ghahramani Z, Jordan MI. Are arm trajectories planned in kinematic or dynamic coordinates? An adaptation study. Experimental Brain Research. 103: 460-70. PMID 7789452 DOI: 10.1007/BF00241505 |
0.621 |
|
1995 |
Wolpert DM, Ghahramani Z, Jordan MI. An internal model for sensorimotor integration. Science (New York, N.Y.). 269: 1880-2. PMID 7569931 DOI: 10.1126/Science.7569931 |
0.654 |
|
1994 |
Wolpert DM, Ghahramani Z, Jordan MI. Perceptual distortion contributes to the curvature of human reaching movements. Experimental Brain Research. 98: 153-6. PMID 8013583 DOI: 10.1007/BF00229120 |
0.599 |
|
Low-probability matches (unlikely to be authored by this person) |
2015 |
Nazabal A, Garcia-Moreno P, Artes-Rodriguez A, Ghahramani Z. Human Activity Recognition by Combining a Small Number of Classifiers. Ieee Journal of Biomedical and Health Informatics. PMID 26208368 DOI: 10.1109/JBHI.2015.2458274 |
0.296 |
|
2006 |
Kim HC, Kim D, Ghahramani Z, Bang SY. Appearance-based gender classification with Gaussian processes Pattern Recognition Letters. 27: 618-626. DOI: 10.1016/j.patrec.2005.09.027 |
0.292 |
|
2010 |
Silva R, Heller K, Ghahramani Z, Airoldi EM. RANKING RELATIONS USING ANALOGIES IN BIOLOGICAL AND INFORMATION NETWORKS. The Annals of Applied Statistics. 4: 615-644. PMID 24587838 DOI: 10.1214/09-Aoas321 |
0.291 |
|
2010 |
Savage RS, Ghahramani Z, Griffin JE, de la Cruz BJ, Wild DL. Discovering transcriptional modules by Bayesian data integration. Bioinformatics (Oxford, England). 26: i158-67. PMID 20529901 DOI: 10.1093/Bioinformatics/Btq210 |
0.283 |
|
2010 |
Ghahramani Z. Bayesian hidden markov models and extensions: Invited talk Conll 2010 - Fourteenth Conference On Computational Natural Language Learning, Proceedings of the Conference. 56. |
0.281 |
|
2016 |
Iwata T, Lloyd JR, Ghahramani Z. Unsupervised Many-to-Many Object Matching for Relational Data. Ieee Transactions On Pattern Analysis and Machine Intelligence. 38: 607-17. PMID 27046500 DOI: 10.1109/TPAMI.2015.2469284 |
0.28 |
|
2018 |
Penfold CA, Sybirna A, Reid JE, Huang Y, Wernisch L, Ghahramani Z, Grant M, Surani MA. Branch-recombinant Gaussian processes for analysis of perturbations in biological time series. Bioinformatics (Oxford, England). 34: i1005-i1013. PMID 30423108 DOI: 10.1093/Bioinformatics/Bty603 |
0.28 |
|
2005 |
Chu W, Ghahramani Z, Falciani F, Wild DL. Biomarker discovery in microarray gene expression data with Gaussian processes. Bioinformatics (Oxford, England). 21: 3385-93. PMID 15937031 DOI: 10.1093/bioinformatics/bti526 |
0.274 |
|
2012 |
Sohn KA, Ghahramani Z, Xing EP. Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach. Genetics. 191: 1295-308. PMID 22649082 DOI: 10.1534/Genetics.112.140228 |
0.273 |
|
2011 |
Van Gael J, Ghahramani Z. Nonparametric hidden Markov models Bayesian Time Series Models. 317-340. DOI: 10.1017/CBO9780511984679.016 |
0.271 |
|
2015 |
Quadrianto N, Ghahramani Z. A Very Simple Safe-Bayesian Random Forest. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1297-303. PMID 26357350 DOI: 10.1109/TPAMI.2014.2362751 |
0.27 |
|
2014 |
Hernández-Lobato JM, Houlsby N, Ghahramani Z. Stochastic inference for scalable probabilistic modeling of binary matrices 31st International Conference On Machine Learning, Icml 2014. 2: 1693-1710. |
0.266 |
|
2010 |
Lippert C, Ghahramani Z, Borgwardt KM. Gene function prediction from synthetic lethality networks via ranking on demand. Bioinformatics (Oxford, England). 26: 912-8. PMID 20154010 DOI: 10.1093/bioinformatics/btq053 |
0.262 |
|
2012 |
Osborne MA, Duvenaud D, Garnett R, Rasmussen CE, Roberts SJ, Ghahramani Z. Active learning of model evidence using Bayesian quadrature Advances in Neural Information Processing Systems. 1: 46-54. |
0.26 |
|
2008 |
Heller KA, Williamson S, Ghahramani Z. Statistical models for partial membership Proceedings of the 25th International Conference On Machine Learning. 392-399. |
0.257 |
|
2014 |
Valera I, Ghahramani Z. General table completion using a Bayesian nonparametric model Advances in Neural Information Processing Systems. 2: 981-989. |
0.257 |
|
2018 |
Wade S, Ghahramani Z. Bayesian Cluster Analysis: Point Estimation and Credible Balls (with Discussion) Bayesian Analysis. 13: 559-626. DOI: 10.1214/17-BA1073 |
0.255 |
|
2015 |
Shah A, Knowles DA, Ghahramani Z. An empirical study of stochastic variational algorithms for the beta bernoulli process 32nd International Conference On Machine Learning, Icml 2015. 2: 1594-1603. |
0.254 |
|
2009 |
Silva R, Ghahramani Z. Factorial mixture of Gaussians and the marginal independence model Journal of Machine Learning Research. 5: 520-527. |
0.254 |
|
2015 |
Lloyd JR, Ghahramani Z. Statistical model criticism using kernel two sample tests Advances in Neural Information Processing Systems. 2015: 829-837. |
0.247 |
|
2010 |
Stegle O, Denby KJ, Cooke EJ, Wild DL, Ghahramani Z, Borgwardt KM. A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 17: 355-67. PMID 20377450 DOI: 10.1089/Cmb.2009.0175 |
0.241 |
|
2009 |
Stepleton T, Ghahramani Z, Gordon G, Lee TS. The block diagonal infinite hidden Markov model Journal of Machine Learning Research. 5: 552-559. |
0.24 |
|
2000 |
Ghahramani Z. Computational neuroscience. Building blocks of movement. Nature. 407: 682-3. PMID 11048700 DOI: 10.1038/35037690 |
0.234 |
|
2009 |
Silva R, Ghahramani Z. The hidden life of latent variables: bayesian learning with mixed graph models Journal of Machine Learning Research. 10: 1187-1238. |
0.226 |
|
2015 |
Tripuraneni N, Gu S, Ge H, Ghahramani Z. Particle Gibbs for infinite Hidden Markov models Advances in Neural Information Processing Systems. 2015: 2395-2403. |
0.22 |
|
2010 |
Rotsos C, Van Gael J, Moore AW, Ghahramani Z. Probabilistic graphical models for semi-supervised traffic classification Iwcmc 2010 - Proceedings of the 6th International Wireless Communications and Mobile Computing Conference. 752-757. DOI: 10.1145/1815396.1815569 |
0.217 |
|
2007 |
Podtelezhnikov AA, Ghahramani Z, Wild DL. Learning about protein hydrogen bonding by minimizing contrastive divergence. Proteins. 66: 588-99. PMID 17109405 DOI: 10.1002/prot.21247 |
0.216 |
|
2012 |
Palla K, Knowles DA, Ghahramani Z. An infinite latent attribute model for network data Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1607-1614. |
0.213 |
|
2014 |
Wu Y, Lobato JMH, Ghahramani Z. Gaussian process volatility model Advances in Neural Information Processing Systems. 2: 1044-1052. |
0.213 |
|
2015 |
Hensman J, De Matthews AG, Filippone M, Ghahramani Z. MCMC for variationally sparse Gaussian processes Advances in Neural Information Processing Systems. 2015: 1648-1656. |
0.211 |
|
2019 |
Vergari A, Molina A, Peharz R, Ghahramani Z, Kersting K, Valera I. Automatic Bayesian Density Analysis Proceedings of the Aaai Conference On Artificial Intelligence. 33: 5207-5215. DOI: 10.1609/aaai.v33i01.33015207 |
0.211 |
|
2001 |
Ghahramani Z, Beal MJ. Propagation algorithms for variational Bayesian learning Advances in Neural Information Processing Systems. |
0.209 |
|
2015 |
Cunningham JP, Ghahramani Z. Linear dimensionality reduction: Survey, insights, and generalizations Journal of Machine Learning Research. 16: 2859-2900. |
0.205 |
|
2013 |
Quadrianto N, Sharmanska V, Knowles DA, Ghahramani Z. The supervised IBP: Neighbourhood preserving infinite latent feature models Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, Uai 2013. 527-536. |
0.203 |
|
2005 |
Chu W, Ghahramani Z. Preference learning with Gaussian processes Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 137-144. |
0.197 |
|
2007 |
Chu W, Sindhwani V, Ghahramani Z, Keerthi SS. Relational learning with Gaussian processes Advances in Neural Information Processing Systems. 289-296. |
0.197 |
|
2012 |
Houlsby N, Hernández-Lobato JM, Huszár F, Ghahramani Z. Collaborative Gaussian processes for preference learning Advances in Neural Information Processing Systems. 3: 2096-2104. |
0.194 |
|
2019 |
Adel T, Valera I, Ghahramani Z, Weller A. One-Network Adversarial Fairness Proceedings of the Aaai Conference On Artificial Intelligence. 33: 2412-2420. DOI: 10.1609/AAAI.V33I01.33012412 |
0.193 |
|
2005 |
Sung J, Bang SY, Choi S, Ghahramani Z. u-likelihood and u-updating algorithms: Statistical inference in latent variable models Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3720: 377-388. |
0.19 |
|
2004 |
Ghahramani Z. Unsupervised learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3176: 72-112. |
0.189 |
|
2007 |
Heller KA, Ghahramani Z. A nonparametric Bayesian approach to modeling overlapping clusters Journal of Machine Learning Research. 2: 187-194. |
0.186 |
|
2012 |
Niu D, Dy JG, Ghahramani Z. A nonparametric Bayesian model for multiple clustering with overlapping feature views Journal of Machine Learning Research. 22: 814-822. |
0.185 |
|
2009 |
Chu W, Ghahramani Z. Probabilistic models for incomplete multi-dimensional arrays Journal of Machine Learning Research. 5: 89-96. |
0.183 |
|
2013 |
Wu Y, Lobato JMH, Ghahramani Z. Dynamic covariance models for multivariate financial time series 30th International Conference On Machine Learning, Icml 2013. 1595-1603. |
0.183 |
|
2015 |
͆cibior A, Ghahramani Z, Gordon AD. Practical probabilistic programming with monads Haskell 2015 - Proceedings of the 8th Acm Sigplan Symposium On Haskell, Co-Located With Icfp 2015. 165-176. DOI: 10.1145/2804302.2804317 |
0.183 |
|
2009 |
Doshi-Velez F, Ghahramani Z. Correlated non-parametric latent feature models Proceedings of the 25th Conference On Uncertainty in Artificial Intelligence, Uai 2009. 143-150. |
0.179 |
|
2015 |
Gu S, Ghahramani Z, Turner RE. Neural adaptive sequential Monte Carlo Advances in Neural Information Processing Systems. 2015: 2629-2637. |
0.178 |
|
2003 |
Jin R, Ghahramani Z. Learning with multiple labels Advances in Neural Information Processing Systems. |
0.176 |
|
2006 |
Silva R, Ghahramani Z. Bayesian inference for Gaussian mixed graph models Proceedings of the 22nd Conference On Uncertainty in Artificial Intelligence, Uai 2006. 453-460. |
0.175 |
|
2005 |
Zhang J, Ghahramani Z, Yang Y. Learning multiple related tasks using latent Independent Component Analysis Advances in Neural Information Processing Systems. 1585-1592. |
0.175 |
|
2003 |
Zhu X, Ghahramani Z, Lafferty J. Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions Proceedings, Twentieth International Conference On Machine Learning. 2: 912-919. |
0.174 |
|
2014 |
Bargi A, Da Xu RY, Ghahramani Z, Piccardi M. A non-parametric conditional factor regression model for multi-dimensional input and response Journal of Machine Learning Research. 33: 77-85. |
0.173 |
|
2012 |
Palla K, Knowles DA, Ghahramani Z. A nonparametric variable clustering model Advances in Neural Information Processing Systems. 4: 2987-2995. |
0.172 |
|
2014 |
Houlsby N, Hernández-Lobato JM, Ghahramani Z. Cold-start active learning with robust ordinal matrix factorization 31st International Conference On Machine Learning, Icml 2014. 3: 1964-1972. |
0.171 |
|
2012 |
Mohamed S, Heller KA, Ghahramani Z. Bayesian and L 1 approaches for sparse unsupervised learning Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 751-758. |
0.166 |
|
2009 |
Silva R, Chu W, Ghahramani Z. Hidden common cause relations in relational learning Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. |
0.166 |
|
2005 |
Zhu X, Kandola J, Ghahramani Z, Lafferty J. Nonparametric transforms of graph kernels for semi-supervised learning Advances in Neural Information Processing Systems. |
0.163 |
|
2015 |
Shah A, Ghahramani Z. Parallel predictive entropy search for batch global optimization of expensive objective functions Advances in Neural Information Processing Systems. 2015: 3330-3338. |
0.161 |
|
2005 |
Murray I, MacKay DJC, Ghahramani Z, Skilling J. Nested sampling for Potts models Advances in Neural Information Processing Systems. 947-954. |
0.158 |
|
2007 |
Beal MJ, Li J, Ghahramani Z, Wild DL. Reconstructing transcriptional networks using gene expression profiling and bayesian state-space models Introduction to Systems Biology. 217-241. DOI: 10.1007/978-1-59745-531-2_12 |
0.154 |
|
2012 |
Wilson AG, Ghahramani Z. Modelling input varying correlations between multiple responses Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7524: 858-861. DOI: 10.1007/978-3-642-33486-3_64 |
0.154 |
|
2013 |
Heaukulani C, Ghahramani Z. Dynamic probabilistic models for latent feature propagation in social networks 30th International Conference On Machine Learning, Icml 2013. 275-283. |
0.151 |
|
2014 |
Lloyd JR, Duvenaud D, Grosse R, Tenenbaum JB, Ghahramani Z. Automatic construction and natural-language description of nonparametric regression models Proceedings of the National Conference On Artificial Intelligence. 2: 1242-1250. |
0.15 |
|
2010 |
Leskovec J, Chakrabarti D, Kleinberg J, Faloutsos C, Ghahramani Z. Kronecker graphs: An approach to modeling networks Journal of Machine Learning Research. 11: 985-1042. |
0.15 |
|
2013 |
Iwata T, Houlsby N, Ghahramani Z. Active learning for interactive visualization Journal of Machine Learning Research. 31: 342-350. |
0.149 |
|
2004 |
Chu W, Ghahramani Z, Wild DL. A graphical model for protein secondary structure prediction Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 161-168. |
0.139 |
|
2015 |
Hernández-Lobato D, Hernández-Lobato JM, Ghahramani Z. A probabilistic model for dirty multi-task feature selection 32nd International Conference On Machine Learning, Icml 2015. 2: 1073-1082. |
0.138 |
|
2006 |
Chu W, Ghahramani Z, Krause R, Wild DL. Identifying protein complexes in high-throughput protein interaction screens using an infinite latent feature model. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 231-42. PMID 17094242 |
0.123 |
|
2009 |
Lippert C, Stegle O, Ghahramani Z, Borgwardt KM. A kernel method for unsupervised structured network inference Journal of Machine Learning Research. 5: 368-375. |
0.121 |
|
2012 |
Wilson AG, Knowles DA, Ghahramani Z. Gaussian process regression networks Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 599-606. |
0.121 |
|
2012 |
Kim HC, Ghahramani Z. Bayesian classifier combination Journal of Machine Learning Research. 22: 619-627. |
0.12 |
|
2000 |
Ghahramani Z, Beai MJ. Variational inference for Bayesian mixtures of factor analysers Advances in Neural Information Processing Systems. 449-455. |
0.118 |
|
2006 |
Azran A, Ghahramani Z. Spectral methods for automatic multiscale data clustering Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1: 190-197. DOI: 10.1109/CVPR.2006.289 |
0.117 |
|
2013 |
Shah A, Ghahramani Z. Determinantal clustering process - A nonparametric Bayesian approach to kernel based semi-supervised clustering Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, Uai 2013. 566-575. |
0.115 |
|
2014 |
Hernández-Lobato JM, Houlsby N, Ghahramani Z. Probabilistic matrix factorization with non-random missing data 31st International Conference On Machine Learning, Icml 2014. 4: 3394-3436. |
0.112 |
|
2014 |
Paydar S, Ghahramani Z, Bolandparvaz S, Khalili H, Abbasi HR. Learning operational strategies in surgery training. Journal of Advances in Medical Education & Professionalism. 2: 92-4. PMID 25512927 |
0.11 |
|
2008 |
Kim HC, Ghahramani Z. Outlier robust Gaussian process classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5342: 896-905. DOI: 10.1007/978-3-540-89689-0_93 |
0.109 |
|
2005 |
Chu W, Ghahramani Z. Gaussian processes for ordinal regression Journal of Machine Learning Research. 6. |
0.108 |
|
2006 |
Azran A, Ghahramani Z. A new approach to data driven clustering Acm International Conference Proceeding Series. 148: 57-64. DOI: 10.1145/1143844.1143852 |
0.108 |
|
2005 |
Snelson E, Ghahramani Z. Sparse Gaussian processes using pseudo-inputs Advances in Neural Information Processing Systems. 1257-1264. |
0.108 |
|
2015 |
Dziugaite GK, Roy DM, Ghahramani Z. Training generative neural networks via maximum mean discrepancy optimization Uncertainty in Artificial Intelligence - Proceedings of the 31st Conference, Uai 2015. 258-267. |
0.105 |
|
2005 |
Heller KA, Ghahramani Z. Bayesian hierarchical clustering Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 297-304. DOI: 10.1145/1102351.1102389 |
0.102 |
|
2002 |
Rasmussen CE, Ghahramani Z. Infinite mixtures of Gaussian process experts Advances in Neural Information Processing Systems. |
0.1 |
|
2007 |
Snelson E, Ghahramani Z. Local and global sparse Gaussian process approximations Journal of Machine Learning Research. 2: 524-531. |
0.099 |
|
2009 |
Doshi-Velez F, Knowles D, Mohamed S, Ghahramani Z. Large scale nonparametric Bayesian inference: Data parallelisation in the Indian Buffet process Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1294-1302. |
0.099 |
|
2013 |
Lopez-Paz D, Hernández-Lobato JM, Ghahramani Z. Gaussian process vine copulas for multivariate dependence 30th International Conference On Machine Learning, Icml 2013. 669-677. |
0.098 |
|
2009 |
Xu Y, Heller KA, Ghahramani Z. Tree-based inference for dirichlet process mixtures Journal of Machine Learning Research. 5: 623-630. |
0.095 |
|
2008 |
Hübler C, Kriegel HP, Borgwardt K, Ghahramani Z. Metropolis algorithms for representative subgraph sampling Proceedings - Ieee International Conference On Data Mining, Icdm. 283-292. DOI: 10.1109/ICDM.2008.124 |
0.095 |
|
2018 |
Ścibior A, Kammar O, Vákár M, Staton S, Yang H, Cai Y, Ostermann K, Moss SK, Heunen C, Ghahramani Z. Denotational validation of higher-order Bayesian inference Proceedings of the Acm On Programming Languages. 2: 1-29. DOI: 10.1145/3158148 |
0.095 |
|
2006 |
Heller KA, Ghahramani Z. A simple bayesian framework for content-based image retrieval Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2: 2110-2117. DOI: 10.1109/CVPR.2006.41 |
0.095 |
|
2012 |
Steinhardt J, Ghahramani Z. Flexible martingale priors for deep hierarchies Journal of Machine Learning Research. 22: 1108-1116. |
0.094 |
|
2009 |
Van Gael J, Vlachos A, Ghahramani Z. The infinite HMM for unsupervised PoS tagging Emnlp 2009 - Proceedings of the 2009 Conference On Empirical Methods in Natural Language Processing: a Meeting of Sigdat, a Special Interest Group of Acl, Held in Conjunction With Acl-Ijcnlp 2009. 678-687. |
0.094 |
|
2014 |
Bratières S, Quadrianto N, Nowozin S, Ghahramani Z. Scalable Gaussian process structured prediction for grid factor graph applications 31st International Conference On Machine Learning, Icml 2014. 2: 1625-1636. |
0.094 |
|
2006 |
Kim HC, Kim D, Ghahramani Z, Bang SY. Gender classification with Bayesian kernel methods Ieee International Conference On Neural Networks - Conference Proceedings. 3371-3376. |
0.092 |
|
2015 |
Hensman J, Matthews AG, Ghahramani Z. Scalable variational Gaussian process classification Journal of Machine Learning Research. 38: 351-360. |
0.092 |
|
2005 |
Ghahramani Z, Heller KA. Bayesian sets Advances in Neural Information Processing Systems. 435-442. |
0.089 |
|
2014 |
Hernández-Lobato JM, Hoffman MW, Ghahramani Z. Predictive entropy search for efficient global optimization of black-box functions Advances in Neural Information Processing Systems. 1: 918-926. |
0.089 |
|
2013 |
Iwata T, Duvenaud D, Ghahramani Z. Warped mixtures for nonparametric cluster shapes Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, Uai 2013. 311-320. |
0.087 |
|
2012 |
Cunningham JP, Ghahramani Z, Rasmussen CE. Gaussian Processes for time-marked time-series data Journal of Machine Learning Research. 22: 255-263. |
0.087 |
|
2012 |
Lloyd JR, Orbanz P, Ghahramani Z, Roy DM. Random function priors for exchangeable arrays with applications to graphs and relational data Advances in Neural Information Processing Systems. 2: 998-1006. |
0.087 |
|
2011 |
Knowles DA, Van Gael J, Ghahramani Z. Message passing algorithms for dirichlet diffusion trees Proceedings of the 28th International Conference On Machine Learning, Icml 2011. 721-728. |
0.086 |
|
2005 |
Snelson E, Ghahramani Z. Compact approximations to Bayesian predictive distributions Icml 2005 - Proceedings of the 22nd International Conference On Machine Learning. 841-848. |
0.083 |
|
2013 |
Duvenaud D, Lloyd JR, Grosse R, Tenenbaum JB, Ghahramani Z. Structure discovery in nonparametric regression through compositional kernel search 30th International Conference On Machine Learning, Icml 2013. 2203-2211. |
0.082 |
|
2007 |
Silva R, Heller KA, Ghahramani Z. Analogical reasoning with relational Bayesian sets Journal of Machine Learning Research. 2: 500-507. |
0.082 |
|
2014 |
Lopez-Paz D, Sra S, Smola AJ, Ghahramani Z, Schölkopf B. Randomized nonlinear component analysis 31st International Conference On Machine Learning, Icml 2014. 4: 3196-3204. |
0.082 |
|
2014 |
Gal Y, Ghahramani Z. Pitfalls in the use of parallel inference for the dirichlet process 31st International Conference On Machine Learning, Icml 2014. 2: 1437-1445. |
0.08 |
|
2004 |
Bourne PE, Allerston CK, Krebs W, Li W, Shindyalov IN, Godzik A, Friedberg I, Liu T, Wild D, Hwang S, Ghahramani Z, Chen L, Westbrook J. The status of structural genomics defined through the analysis of current targets and structures. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 375-86. PMID 14992518 DOI: 10.1142/9789812704856_0036 |
0.079 |
|
2004 |
Snelson E, Rasmussen CE, Ghahramani Z. Warped Gaussian processes Advances in Neural Information Processing Systems. |
0.079 |
|
2006 |
Snelson E, Ghahramani Z. Variable noise and dimensionality reduction for sparse Gaussian processes Proceedings of the 22nd Conference On Uncertainty in Artificial Intelligence, Uai 2006. 461-468. |
0.078 |
|
2009 |
Eaton F, Ghahramani Z. Choosing a variable to clamp: Approximate inference using conditioned belief propagation Journal of Machine Learning Research. 5: 145-152. |
0.075 |
|
2002 |
Korenberg AT, Ghahramani Z. A Bayesian view of motor adaptation Cahiers De Psychologie Cognitive. 21: 537-564. |
0.074 |
|
2010 |
Turner R, Ghahramani Z, Bottone S. Fast online anomaly detection using scan statistics Proceedings of the 2010 Ieee International Workshop On Machine Learning For Signal Processing, Mlsp 2010. 385-390. DOI: 10.1109/MLSP.2010.5589151 |
0.073 |
|
2003 |
Rasmussen CE, Ghahramani Z. Bayesian Monte Carlo Advances in Neural Information Processing Systems. |
0.072 |
|
2015 |
Quadrianto N, Ghahramani Z. A very simple safe-Bayesian random forest Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1297-1303. DOI: 10.1109/TPAMI.2014.2362751 |
0.072 |
|
2015 |
Steinruecken C, Ghahramani Z, MacKay D. Improving PPM with Dynamic Parameter Updates Data Compression Conference Proceedings. 2015: 193-202. DOI: 10.1109/DCC.2015.77 |
0.071 |
|
2006 |
Chu W, Keerthi SS, Ong CJ, Ghahramani Z. Bayesian support vector machines for feature ranking and selection Studies in Fuzziness and Soft Computing. 207: 403-418. |
0.068 |
|
2013 |
Bousmalis K, Zafeiriou S, Morency LP, Pantic M, Ghahramani Z. Variational hidden conditional random fields with coupled Dirichlet Process Mixtures Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8189: 531-547. DOI: 10.1007/978-3-642-40991-2_34 |
0.066 |
|
2015 |
Mohajer Y, Ghahramani Z, Fine ML. Pectoral sound generation in the blue catfish Ictalurus furcatus. Journal of Comparative Physiology. a, Neuroethology, Sensory, Neural, and Behavioral Physiology. 201: 305-15. PMID 25502507 DOI: 10.1007/S00359-014-0970-7 |
0.065 |
|
2012 |
Zhang Y, Sutton C, Storkey A, Ghahramani Z. Continuous relaxations for discrete Hamiltonian Monte Carlo Advances in Neural Information Processing Systems. 4: 3194-3202. |
0.063 |
|
2014 |
Palla K, Knowles DA, Ghahramani Z. A reversible infinite HMM using normalised random measures 31st International Conference On Machine Learning, Icml 2014. 5: 4090-4107. |
0.062 |
|
2010 |
Williamson S, Orbanz P, Ghahramani Z. Dependent Indian buffet processes Journal of Machine Learning Research. 9: 924-931. |
0.054 |
|
2012 |
Póczos B, Ghahramani Z, Schneider J. Copula-based kernel dependency measures Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 775-782. |
0.052 |
|
2018 |
Ścibior A, Kammar O, Ghahramani Z. Functional programming for modular Bayesian inference Proceedings of the Acm On Programming Languages. 2: 1-29. DOI: 10.1145/3236778 |
0.05 |
|
2015 |
Bousmalis K, Zafeiriou S, Morency LP, Pantic M, Ghahramani Z. Variational infinite hidden conditional random fields Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1917-1929. DOI: 10.1109/TPAMI.2014.2388228 |
0.05 |
|
2011 |
Wilson AG, Ghahramani Z. Generalised Wishart processes Proceedings of the 27th Conference On Uncertainty in Artificial Intelligence, Uai 2011. 736-744. |
0.049 |
|
2009 |
Mohamed S, Heller K, Ghahramani Z. Bayesian exponential family PCA Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1089-1096. |
0.049 |
|
2012 |
Bahramisharif A, Van Gerven MAJ, Schoffelen JM, Ghahramani Z, Heskes T. The dynamic beamformer Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7263: 148-155. DOI: 10.1007/978-3-642-34713-9_19 |
0.049 |
|
2004 |
Qi Y, Minka TP, Picard RW, Ghahramani Z. Predictive automatic relevance determination by expectation propagation Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 671-678. |
0.048 |
|
2010 |
Wilson AG, Ghahramani Z. Copula processes Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.048 |
|
2011 |
Zabih R, Ghahramani Z, Kang SB, Matas J. IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's note Ieee Transactions On Pattern Analysis and Machine Intelligence. 33: 865-866. DOI: 10.1109/TPAMI.2011.60 |
0.046 |
|
2010 |
Zabih R, Matas J, Ghahramani Z. IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's Note Ieee Transactions On Pattern Analysis and Machine Intelligence. 32: 769. DOI: 10.1109/TPAMI.2010.82 |
0.046 |
|
2010 |
Zabih R, Matas J, Ghahramani Z. IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's Note Ieee Transactions On Pattern Analysis and Machine Intelligence. 32: 1345-1346. DOI: 10.1109/TPAMI.2010.124 |
0.046 |
|
2009 |
Doshi-Velez F, Ghahramani Z. Accelerated sampling for the Indian buffet process Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 273-280. DOI: 10.1145/1553374.1553409 |
0.045 |
|
2014 |
Shah A, Wilson AG, Ghahramani Z. Student-t processes as alternatives to Gaussian processes Journal of Machine Learning Research. 33: 877-885. |
0.041 |
|
2009 |
Stegle O, Denby KJ, McHattie S, Mead A, Wild DL, Ghahramani Z, Borgwardt KM. Discovering temporal patterns of differential gene expression in microarray time series Gcb 2009 - German Conference On Bioinformatics 2009. 133-142. |
0.04 |
|
2015 |
Forlano PM, Ghahramani ZN, Monestime CM, Kurochkin P, Chernenko A, Milkis D. Catecholaminergic innervation of central and peripheral auditory circuitry varies with reproductive state in female midshipman fish, Porichthys notatus. Plos One. 10: e0121914. PMID 25849450 DOI: 10.1371/Journal.Pone.0121914 |
0.04 |
|
2006 |
Kurata D, Nankaku Y, Tokuda K, Kitamura T, Ghahramani Z. Face recognition based on separable lattice HMMS Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 5: V737-V740. |
0.04 |
|
2006 |
Murray I, Ghahramani Z, MacKay DJC. MCMC for doubly-intractable distributions Proceedings of the 22nd Conference On Uncertainty in Artificial Intelligence, Uai 2006. 359-366. |
0.04 |
|
2013 |
Reed C, Ghahramani Z. Scaling the Indian buffet process via submodular maximization 30th International Conference On Machine Learning, Icml 2013. 2050-2058. |
0.038 |
|
2015 |
Ghahramani ZN, Timothy M, Kaur G, Gorbonosov M, Chernenko A, Forlano PM. Catecholaminergic Fiber Innervation of the Vocal Motor System Is Intrasexually Dimorphic in a Teleost with Alternative Reproductive Tactics. Brain, Behavior and Evolution. 86: 131-44. PMID 26355302 DOI: 10.1159/000438720 |
0.036 |
|
2011 |
Knowles DA, Ghahramani Z. Pitman-Yor diffusion trees Proceedings of the 27th Conference On Uncertainty in Artificial Intelligence, Uai 2011. 410-418. |
0.034 |
|
2014 |
Ghahramani ZN, Mohajer Y, Fine ML. Developmental variation in sound production in water and air in the blue catfish Ictalurus furcatus. The Journal of Experimental Biology. 217: 4244-51. PMID 25324337 DOI: 10.1242/Jeb.112946 |
0.03 |
|
2011 |
Zabih R, Matas J, Ghahramani Z. State of the journal Ieee Transactions On Pattern Analysis and Machine Intelligence. 33: 1-2. DOI: 10.1109/TPAMI.2011.7 |
0.03 |
|
2008 |
Kriegman DJ, Fleet D, Ghahramani Z. Editorial - State of the transactions Ieee Transactions On Pattern Analysis and Machine Intelligence. 30: 193-194. DOI: 10.1109/TPAMI.2008.13 |
0.028 |
|
2014 |
Heaukulani C, Knowles DA, Ghahramani Z. Beta diffusion trees 31st International Conference On Machine Learning, Icml 2014. 5: 3821-3829. |
0.025 |
|
2009 |
Zabih R, Ghahramani Z, Matas J. Introduction of New Associate Editors Ieee Transactions On Pattern Analysis and Machine Intelligence. 31: 961-963. DOI: 10.1109/tpami.2009.90 |
0.016 |
|
2009 |
Zabih R, Matas J, Ghahramani Z. Introduction of New Associate Editors Ieee Transactions On Pattern Analysis and Machine Intelligence. 31: 1345-1346. DOI: 10.1109/tpami.2009.130 |
0.016 |
|
2008 |
Kriegman DJ, Fleet D, Ghahramani Z. Introduction of New Associate Editors Ieee Transactions On Pattern Analysis and Machine Intelligence. 30: 561-561. DOI: 10.1109/TPAMI.2008.43 |
0.016 |
|
2010 |
Bratières S, Van Gael J, Vlachos A, Ghahramani Z. Scaling the iHMM: Parallelization versus Hadoop Proceedings - 10th Ieee International Conference On Computer and Information Technology, Cit-2010, 7th Ieee International Conference On Embedded Software and Systems, Icess-2010, Scalcom-2010. 1235-1240. DOI: 10.1109/CIT.2010.223 |
0.013 |
|
2014 |
Paydar S, Ghahramani Z. Is the study of mortality reduction alone indicating the effectiveness of the guideline? Injury. 45: 2114. PMID 24875631 DOI: 10.1016/j.injury.2014.04.010 |
0.01 |
|
2014 |
Paydar S, Ghahramani Z. Cancer diagnosis disclosure: What is the right thing to do? Middle East Journal of Cancer. 5: 109-110. |
0.01 |
|
2014 |
Welling M, Ghahramani Z, Cortes C, Lawrence N, Weinberger K. Preface Advances in Neural Information Processing Systems. 1: xxxi-xxxiv. |
0.01 |
|
2011 |
Zabih R, Ghahramani Z, Kang SB, Matas J. Editor's note Ieee Transactions On Pattern Analysis and Machine Intelligence. 33: 1697-1698. DOI: 10.1109/TPAMI.2011.139 |
0.01 |
|
2001 |
Rasmussen CE, Ghahramani Z. Occam's razor Advances in Neural Information Processing Systems. |
0.01 |
|
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