My primary interest lies in uncovering fundamental algorithms and principles of intelligence and intelligent behavior - be it biological or artificial. My current work revolves around theories of perception in the brain - specifically that the brain performs perception via probabilistic inference. I am interested in modeling and evaluating these theories on large scale neurophysiological recordings from the visual cortex using modern probabilistic machine learning methods.
Lab members are shown in this color.
2024
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Finn Schmidt, Suhas Shrinivasan1, Polina Turishcheva1, Fabian Sinz
Modeling dynamic neural activity by combining naturalistic video stimuli and stimulus-independent latent factors
NeuReps @ NeurIPS 2024
, equal contribution: 1
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Suhas Shrinivasan, Ralf Häfner, Fabian Sinz, Edgar Y. Walker
Towards zero-shot adaptation of predictive models of neurons encoding posterior probability
NeurNeuroAI @ NeurIPS 2024
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Jiakun Fu, Suhas Shrinivasan, Luca Baroni, Zhuokun Ding, Paul G. Fahey, Paweł Pierzchlewicz, Kayla Ponder, Rachel Froebe, Lydia Ntanavara, Taliah Muhammad, Konstantin F Willeke, Eric Wang, Zhiwei Ding, Dat T. Tran, Stelios Papadopoulos, Saumil Patel, Jacob Reimer, Alexander S. Ecker, Xaq Pitkow, Jan Antolik, Fabian H. Sinz, Ralf M. Haefner, Andreas S. Tolias, Katrin Franke
Pattern completion and disruption characterize contextual modulation in the visual cortex
bioRxiv
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2023
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Suhas Shrinivasan, Konstantin-Klemens Lurz, Kelli Restivo, George Denfield, Andreas S. Tolias, Edgar Y. Walker1, Fabian H. Sinz1
Taking the neural sampling code very seriously: A data-driven approach for assessing generative models of the visual system
NeurIPS
, equal contribution: 1
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Suhas Shrinivasan, Andreas S. Tolias, Edgar Y. Walker*, Fabian H. Sinz*
Fitting normative neural sampling hypothesis models to neuronal response data
COSYNE 2023
, equal contribution: *
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2022
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Arne Nix, Suhas Shrinivasan, Edgar Y. Walker, Fabian H. Sinz
Can Functional Transfer Methods Capture Simple Inductive Biases?
AISTATS 2022
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