← Search

Suhas Shrinivasan

3 accepted papers

2025

Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors

NeurIPS 2025poster

The neural activity in the visual processing is influenced by both external stimuli and internal brain states. Ideally, a neural predictive model should account for both of them. Currently, there are no dynamic encoding models that explicitly model a latent state and the entire neuronal response d…

Cited by 2Source ↗Scholar ↗
2023

Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system

NeurIPS 2023poster

Prevailing theories of perception hypothesize that the brain implements perception via Bayesian inference in a generative model of the world. One prominent theory, the Neural Sampling Code (NSC), posits that neuronal responses to a stimulus represent samples from the posterior distribution over late…

Cited by 5Source ↗PDF ↗Scholar ↗
2022

Can Functional Transfer Methods Capture Simple Inductive Biases?

AISTATS 2022poster

Transferring knowledge embedded in trained neural networks is a core problem in areas like model compression and continual learning. Among knowledge transfer approaches, functional transfer methods such as knowledge distillation and representational distance learning are particularly promising, sinc…