Kanaka Rajan
Affiliations: | Columbia University, New York, NY |
Area:
Computational neuroscienceGoogle:
"Kanaka Rajan"Mean distance: 14.07 (cluster 17) | S | N | B | C | P |
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Publications
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| DePasquale B, Cueva CJ, Rajan K, et al. (2018) full-FORCE: A target-based method for training recurrent networks. Plos One. 13: e0191527 |
| Rajan K, Harvey CD, Tank DW. (2016) Recurrent Network Models of Sequence Generation and Memory. Neuron |
| Rajan K, Bialek W. (2013) Maximally informative "stimulus energies" in the analysis of neural responses to natural signals. Plos One. 8: e71959 |
| Rajan K, Marre O, Tka?ik G. (2013) Learning quadratic receptive fields from neural responses to natural stimuli. Neural Computation. 25: 1661-92 |
| Dass S, Holi MS, Rajan KS. (2013) Comparative study of the brainstem auditory evoked responses in infants and adults International Conference On Communication and Signal Processing, Iccsp 2013 - Proceedings. 372-376 |
| Abbott LF, Rajan K, Sompolinsky H. (2011) Interactions between Intrinsic and Stimulus-Evoked Activity in Recurrent Neural Networks The Dynamic Brain: An Exploration of Neuronal Variability and Its Functional Significance |
| Rajan K, Abbott LF, Sompolinsky H. (2010) Stimulus-dependent suppression of chaos in recurrent neural networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 82: 011903 |
| Chandrasekhar G, Rahim BA, Shaik F, et al. (2010) Ricean code based compression method for bayer CFA images Proceedings of the International Conference On "Recent Advances in Space Technology Services and Climate Change - 2010", Rsts and Cc-2010. 102-106 |
| Dass S, Holi MS, Rajan KS. (2010) Review article: Various methods of analysis on ABRs Wce 2010 - World Congress On Engineering 2010. 2: 925-930 |
| Rajan K, Abbott LF, Sompolinsky H. (2010) Inferring stimulus selectivity from the spatial structure of neural network dynamics Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 |