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← Authors

Blake Richards

13 papers · 2018–2024 · 3 conferences · across top CS/AI conferences

Achievements

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+5 more ↓ 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (32) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (3) πŸƒ Academic Marathon (6)
🧭 Keyword Pioneer 🐝 Cross-Pollinator (13) πŸ—ƒοΈ Keyword Collector (70) πŸ’Ž Century Club (13) πŸ”₯ Unstoppable (5)

Conferences

NIPS (11) ICLR (1) ICML (1)

Top co-authors

Guillaume Lajoie (3) Arna Ghosh (3) Yoshua Bengio (2) Mehdi Azabou (2) Christopher Pack (2) Shahab Bakhtiari (2) Eva Dyer (2) Patrick Mineault (2) Irina Rish (2) Timothy Lillicrap (2)

Keywords

self-supervised learning (3) biological plausibility (2) credit assignment (2) recurrent neural network (2) neural decoding (2) neural network (2) adversarial robustness (1) feature learning (1) contrastive learning (1) domain adaptation (1) computational neuroscience (1) local learning (1) visual cortex (1) prototype learning (1) transfer learning (1) multi-task learning (1) brain-computer interface (1) loss landscape (1) gradient descent (1) neural dynamics (1)

Papers

Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution NIPS 2024 A Unified, Scalable Framework for Neural Population Decoding NIPS 2023 Learning better with Dale’s Law: A Spectral Perspective NIPS 2023 Formalizing locality for normative synaptic plasticity models NIPS 2023 Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL NIPS 2023 Towards Scaling Difference Target Propagation by Learning Backprop Targets ICML 2022 $\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay NIPS 2022 Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules NIPS 2022 Your head is there to move you around: Goal-driven models of the primate dorsal pathway NIPS 2021 The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning NIPS 2021 Adversarial Feature Desensitization NIPS 2021 Spike-based causal inference for weight alignment ICLR 2020 Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures NIPS 2018