| Year |
Citation |
Score |
| 2020 |
Kugele A, Pfeil T, Pfeiffer M, Chicca E. Efficient Processing of Spatio-Temporal Data Streams With Spiking Neural Networks. Frontiers in Neuroscience. 14: 439. PMID 32431592 DOI: 10.3389/Fnins.2020.00439 |
0.694 |
|
| 2020 |
Kassraian-Fard P, Pfeiffer M, Bauer R. A generative growth model for thalamocortical axonal branching in primary visual cortex. Plos Computational Biology. 16: e1007315. PMID 32053598 DOI: 10.1371/Journal.Pcbi.1007315 |
0.676 |
|
| 2019 |
Soldado-Magraner S, Brandalise F, Honnuraiah S, Pfeiffer M, Moulinier M, Gerber U, Douglas R. Conditioning by Subthreshold Synaptic Input Changes the Intrinsic Firing Pattern of CA3 Hippocampal Neurons. Journal of Neurophysiology. PMID 31721636 DOI: 10.1152/Jn.00506.2019 |
0.602 |
|
| 2018 |
Pfeiffer M, Pfeil T. Deep Learning With Spiking Neurons: Opportunities and Challenges. Frontiers in Neuroscience. 12: 774. PMID 30410432 DOI: 10.3389/Fnins.2018.00774 |
0.463 |
|
| 2018 |
Beggel L, Kausler BX, Schiegg M, Pfeiffer M, Bischl B. Time series anomaly detection based on shapelet learning Computational Statistics. 34: 945-976. DOI: 10.1007/S00180-018-0824-9 |
0.362 |
|
| 2017 |
Rueckauer B, Lungu IA, Hu Y, Pfeiffer M, Liu SC. Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification. Frontiers in Neuroscience. 11: 682. PMID 29375284 DOI: 10.3389/Fnins.2017.00682 |
0.415 |
|
| 2017 |
Kainz P, Pfeiffer M, Urschler M. Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization. Peerj. 5: e3874. PMID 29018612 DOI: 10.7717/Peerj.3874 |
0.334 |
|
| 2016 |
Lee JH, Delbruck T, Pfeiffer M. Training Deep Spiking Neural Networks Using Backpropagation. Frontiers in Neuroscience. 10: 508. PMID 27877107 DOI: 10.3389/Fnins.2016.00508 |
0.411 |
|
| 2015 |
Stromatias E, Neil D, Pfeiffer M, Galluppi F, Furber SB, Liu SC. Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms. Frontiers in Neuroscience. 9: 222. PMID 26217169 DOI: 10.3389/Fnins.2015.00222 |
0.416 |
|
| 2015 |
Pfeiffer M, Betizeau M, Waltispurger J, Pfister SS, Douglas RJ, Kennedy H, Dehay C. Unsupervised lineage-based characterization of primate precursors reveals high proliferative and morphological diversity in the OSVZ. The Journal of Comparative Neurology. PMID 26053631 DOI: 10.1002/Cne.23820 |
0.558 |
|
| 2015 |
Lagorce X, Ieng SH, Clady X, Pfeiffer M, Benosman RB. Spatiotemporal features for asynchronous event-based data. Frontiers in Neuroscience. 9: 46. PMID 25759637 DOI: 10.3389/Fnins.2015.00046 |
0.363 |
|
| 2015 |
Binas J, Indiveri G, Pfeiffer M. Local structure supports learning of deterministic behavior in recurrent neural networks Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P195 |
0.638 |
|
| 2015 |
Binas J, Indiveri G, Pfeiffer M. Local structure helps learning optimized automata in recurrent neural networks Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280714 |
0.55 |
|
| 2014 |
Galluppi F, Lagorce X, Stromatias E, Pfeiffer M, Plana LA, Furber SB, Benosman RB. A framework for plasticity implementation on the SpiNNaker neural architecture. Frontiers in Neuroscience. 8: 429. PMID 25653580 DOI: 10.3389/Fnins.2014.00429 |
0.456 |
|
| 2014 |
Bauer R, Zubler F, Pfister S, Hauri A, Pfeiffer M, Muir DR, Douglas RJ. Developmental self-construction and -configuration of functional neocortical neuronal networks. Plos Computational Biology. 10: e1003994. PMID 25474693 DOI: 10.1371/Journal.Pcbi.1003994 |
0.692 |
|
| 2014 |
Lee JH, Delbruck T, Pfeiffer M, Park PK, Shin CW, Ryu HE, Kang BC. Real-time gesture interface based on event-driven processing from stereo silicon retinas. Ieee Transactions On Neural Networks and Learning Systems. 25: 2250-63. PMID 25420246 DOI: 10.1109/Tnnls.2014.2308551 |
0.346 |
|
| 2014 |
Binas J, Rutishauser U, Indiveri G, Pfeiffer M. Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity. Frontiers in Computational Neuroscience. 8: 68. PMID 25071538 DOI: 10.3389/Fncom.2014.00068 |
0.627 |
|
| 2013 |
O'Connor P, Neil D, Liu SC, Delbruck T, Pfeiffer M. Real-time classification and sensor fusion with a spiking deep belief network. Frontiers in Neuroscience. 7: 178. PMID 24115919 DOI: 10.3389/Fnins.2013.00178 |
0.4 |
|
| 2013 |
Nessler B, Pfeiffer M, Buesing L, Maass W. Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity. Plos Computational Biology. 9: e1003037. PMID 23633941 DOI: 10.1371/Journal.Pcbi.1003037 |
0.745 |
|
| 2013 |
Sheik S, Pfeiffer M, Stefanini F, Indiveri G. Spatio-temporal spike pattern classification in neuromorphic systems Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8064: 262-273. DOI: 10.1007/978-3-642-39802-5-23 |
0.642 |
|
| 2012 |
Pfeiffer M, Hartbauer M, Lang AB, Maass W, Römer H. Probing real sensory worlds of receivers with unsupervised clustering. Plos One. 7: e37354. PMID 22701566 DOI: 10.1371/Journal.Pone.0037354 |
0.546 |
|
| 2010 |
Pfeiffer M, Nessler B, Douglas RJ, Maass W. Reward-modulated Hebbian learning of decision making. Neural Computation. 22: 1399-444. PMID 20141476 DOI: 10.1162/Neco.2010.03-09-980 |
0.73 |
|
| 2009 |
Nessler B, Pfeiffer M, Maass W. Hebbian learning of Bayes optimal decisions Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1169-1176. |
0.716 |
|
| 2009 |
Nessler B, Pfeiffer M, Maass W. STDP enables spiking neurons to detect hidden causes of their inputs Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 1357-1365. |
0.725 |
|
| 2007 |
Neumann G, Pfeiffer M, Maass W. Efficient continuous-time reinforcement learning with adaptive state graphs Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4701: 250-261. |
0.473 |
|
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