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Blake A. Richards
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- affiliation: McGill University, Montreal, QC, Canada
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2020 – today
- 2024
- [c18]Nanda H. Krishna
, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie:
Sufficient conditions for offline reactivation in recurrent neural networks. ICLR 2024 - [c17]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR 2024 - [i22]David Raposo, Samuel Ritter, Blake A. Richards, Timothy P. Lillicrap, Peter Conway Humphreys, Adam Santoro:
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models. CoRR abs/2404.02258 (2024) - [i21]Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake A. Richards, Irina Rish, Özgür Simsek:
Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent. CoRR abs/2407.12161 (2024) - [i20]Yizi Zhang, Yanchen Wang, Donato Jimenez-Beneto, Zixuan Wang, Mehdi Azabou, Blake A. Richards, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz:
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution. CoRR abs/2407.14668 (2024) - [i19]Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake A. Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento:
Multi-agent cooperation through learning-aware policy gradients. CoRR abs/2410.18636 (2024) - [i18]Raymond Chua, Arna Ghosh, Christos Kaplanis, Blake A. Richards, Doina Precup:
Learning Successor Features the Simple Way. CoRR abs/2410.22133 (2024) - 2023
- [j8]Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake Aaron Richards:
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad P. Körding, Blake Aaron Richards:
How gradient estimator variance and bias impact learning in neural networks. ICLR 2023 - [c15]Chen Sun, Wannan Yang, Thomas Jiralerspong, Dane Malenfant, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake A. Richards:
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL. NeurIPS 2023 - [c14]Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer:
A Unified, Scalable Framework for Neural Population Decoding. NeurIPS 2023 - [c13]Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake A. Richards, Guillaume Lajoie:
Formalizing locality for normative synaptic plasticity models. NeurIPS 2023 - [c12]Pingsheng Li, Jonathan Cornford, Arna Ghosh, Blake A. Richards:
Learning better with Dale's Law: A Spectral Perspective. NeurIPS 2023 - [i17]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR abs/2305.19394 (2023) - [i16]Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael J. Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer:
A Unified, Scalable Framework for Neural Population Decoding. CoRR abs/2310.16046 (2023) - [i15]Kumar Krishna Agrawal, Arna Ghosh, Adam Oberman, Blake A. Richards:
Addressing Sample Inefficiency in Multi-View Representation Learning. CoRR abs/2312.10725 (2023) - 2022
- [j7]Blake A. Richards, Timothy P. Lillicrap:
The Brain-Computer Metaphor Debate Is Useless: A Matter of Semantics. Frontiers Comput. Sci. 4: 810358 (2022) - [j6]Annik Yalnizyan-Carson, Blake A. Richards:
Forgetting Enhances Episodic Control With Structured Memories. Frontiers Comput. Neurosci. 16: 757244 (2022) - [c11]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. AAAI 2022: 6829-6837 - [c10]Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio:
Towards Scaling Difference Target Propagation by Learning Backprop Targets. ICML 2022: 5968-5987 - [c9]Kumar Krishna Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake A. Richards:
$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay. NeurIPS 2022 - [c8]Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie:
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. NeurIPS 2022 - [i14]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. CoRR abs/2201.01836 (2022) - [i13]Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio:
Towards Scaling Difference Target Propagation by Learning Backprop Targets. CoRR abs/2201.13415 (2022) - [i12]Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal, Blake A. Richards:
Investigating Power laws in Deep Representation Learning. CoRR abs/2202.05808 (2022) - [i11]Josh Abramson
Evaluating Multimodal Interactive Agents. CoRR abs/2205.13274 (2022) - [i10]Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie:
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR abs/2206.00823 (2022) - [i9]Giancarlo Kerg, Sarthak Mittal, David Rolnick
On Neural Architecture Inductive Biases for Relational Tasks. CoRR abs/2206.05056 (2022) - [i8]Chen Sun, Wannan Yang, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake A. Richards:
Contrastive introspection (ConSpec) to rapidly identify invariant steps for success. CoRR abs/2210.05845 (2022) - [i7]Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR abs/2210.08340 (2022) - [i6]Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake A. Richards:
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. CoRR abs/2211.16607 (2022) - 2021
- [j5]Laura E. Suárez
Learning function from structure in neuromorphic networks. Nat. Mach. Intell. 3(9): 771-786 (2021) - [j4]Luke Y. Prince, Blake A. Richards:
The overfitted brain hypothesis. Patterns 2(5): 100268 (2021) - [c7]Jonathan Cornford, Damjan Kalajdzievski, Marco Leite, Amélie Lamarquette, Dimitri Michael Kullmann, Blake Aaron Richards:
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units. ICLR 2021 - [c6]Olivier Tessier-Larivière, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie, Blake A. Richards:
PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks. NER 2021: 778-782 - [c5]Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake A. Richards, Irina Rish:
Adversarial Feature Desensitization. NeurIPS 2021: 10665-10677 - [c4]Shahab Bakhtiari, Patrick J. Mineault, Timothy P. Lillicrap, Christopher C. Pack, Blake A. Richards:
The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning. NeurIPS 2021: 25164-25178 - [c3]Patrick J. Mineault, Shahab Bakhtiari, Blake A. Richards, Christopher C. Pack:
Your head is there to move you around: Goal-driven models of the primate dorsal pathway. NeurIPS 2021: 28757-28771 - [i5]Luke Y. Prince, Ellen Boven, Roy Henha Eyono, Arna Ghosh, Joe Pemberton, Franz Scherr, Claudia Clopath, Rui Ponte Costa, Wolfgang Maass, Blake A. Richards, Cristina Savin, Katharina Anna Wilmes:
CCN GAC Workshop: Issues with learning in biological recurrent neural networks. CoRR abs/2105.05382 (2021) - [i4]Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake A. Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint, Michiel van de Panne:
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. CoRR abs/2110.15245 (2021) - 2020
- [c2]Jordan Guerguiev, Konrad P. Körding, Blake A. Richards:
Spike-based causal inference for weight alignment. ICLR 2020 - [i3]Pouya Bashivan, Blake A. Richards, Irina Rish:
Adversarial Feature Desensitization. CoRR abs/2006.04621 (2020)
2010 – 2019
- 2019
- [j3]Blake A. Richards:
Moving beyond reward prediction errors. Nat. Mach. Intell. 1(5): 204-205 (2019) - [i2]Jordan Guerguiev, Konrad P. Körding, Blake A. Richards:
Spike-based causal inference for weight alignment. CoRR abs/1910.01689 (2019) - 2018
- [j2]Nathan Insel, Jordan Guerguiev
Irrelevance by inhibition: Learning, computation, and implications for schizophrenia. PLoS Comput. Biol. 14(8) (2018) - [c1]Sergey Bartunov, Adam Santoro, Blake A. Richards, Luke Marris, Geoffrey E. Hinton, Timothy P. Lillicrap:
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. NeurIPS 2018: 9390-9400 - [i1]Sergey Bartunov, Adam Santoro, Blake A. Richards, Geoffrey E. Hinton, Timothy P. Lillicrap:
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures. CoRR abs/1807.04587 (2018) - 2012
- [j1]John Vervaeke, Timothy P. Lillicrap, Blake A. Richards:
Relevance Realization and the Emerging Framework in Cognitive Science. J. Log. Comput. 22(1): 79-99 (2012)
Coauthor Index
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