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ORCIDElad Schneidman
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2020 – today
- 2022
[c5]Adam Haber, Elad Schneidman:
The computational and learning benefits of Daleian neural networks. NeurIPS 2022- 2021
- [c4]Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, Elad Schneidman:
Estimating the Unique Information of Continuous Variables. NeurIPS 2021: 20295-20307 - [i2]Ari Pakman
, Dar Gilboa, Elad Schneidman:
Estimating the Unique Information of Continuous Variables. CoRR abs/2102.00218 (2021) - 2020
- [i1]Benjamin Brazowski, Elad Schneidman:
Collective Learning by Ensembles of Altruistic Diversifying Neural Networks. CoRR abs/2006.11671 (2020)
2010 – 2019
- 2014
- [j5]Gasper Tkacik, Olivier Marre, Dario Amodei, Elad Schneidman, William Bialek, Michael J. Berry II:
Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput. Biol. 10(1) (2014) - 2013
- [j4]Einat Granot-Atedgi, Gasper Tkacik, Ronen Segev, Elad Schneidman:
Stimulus-dependent Maximum Entropy Models of Neural Population Codes. PLoS Comput. Biol. 9(3) (2013) - 2011
- [j3]Adi Shklarsh, Gil Ariel, Elad Schneidman, Eshel Ben-Jacob:
Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions. PLoS Comput. Biol. 7(9) (2011)
2000 – 2009
- 2002
- [j2]Shlomo Dubnov, Ran El-Yaniv, Yoram Gdalyahu, Elad Schneidman, Naftali Tishby, Golan Yona:
A New Nonparametric Pairwise Clustering Algorithm Based on Iterative Estimation of Distance Profiles. Mach. Learn. 47(1): 35-61 (2002) - [c3]Elad Schneidman, William Bialek, Michael J. Berry II:
An Information Theoretic Approach to the Functional Classification of Neurons. NIPS 2002: 197-204 - 2000
- [c2]Elad Schneidman, Naama Brenner, Naftali Tishby, Robert R. de Ruyter van Steveninck, William Bialek:
Universality and Individuality in a Neural Code. NIPS 2000: 159-165
1990 – 1999
- 1999
- [c1]Elad Schneidman, Idan Segev, Naftali Tishby:
Information Capacity and Robustness of Stochastic Neuron Models. NIPS 1999: 178-184 - 1998
- [j1]Elad Schneidman, Barry Freedman, Idan Segev:
Channel Stochasticity May Be Critical in Determining the Reliability and Precision of Spike Timing. Neural Comput. 10(7): 1679-1703 (1998)
Coauthor Index
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