1 citations · 2 across the 7 of their papers we have counts for
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A Variational Manifold Embedding Framework for Nonlinear Dimensionality Reduction
John J. Vastola, Samuel J. Gershman, Kanaka Rajan
Dimensionality reduction algorithms like principal component analysis (PCA) are workhorses of machine learning and neuroscience, but each has well-known limitations. Variants of PC…
Active Electrosensing and Communication in MARL-trained Weakly Electric Fish Collectives
Satpreet H. Singh, Sonja Johnson-Yu, Zhouyang Lu +7
How complex collective behavior emerges from individual interactions is a fundamental scientific question, but experimental cost and difficulty of simultaneous multi-brain recordin…
InputDSA: Demixing then Comparing Recurrent and Externally Driven Dynamics
Ann Huang, Mitchell Ostrow, Satpreet H. Singh +3
In control problems and basic scientific modeling, it is important to compare observations with dynamical simulations. For example, comparing two neural systems can shed light on t…
Gradient Descent as Loss Landscape Navigation: a Normative Framework for Deriving Learning Rules
John J. Vastola, Samuel J. Gershman, Kanaka Rajan
Learning rules -- prescriptions for updating model parameters to improve performance -- are typically assumed rather than derived. Why do some learning rules work better than other…
Dissecting Larval Zebrafish Hunting using Deep Reinforcement Learning Trained RNN Agents
Raaghav Malik, Satpreet H. Singh, Sonja Johnson-Yu +4
Larval zebrafish hunting provides a tractable setting to study how ecological and energetic constraints shape adaptive behavior in both biological brains and artificial agents. Her…