Stochastic Gradient Descent-Induced Drift of Representation in a Two-Layer Neural Network

no code implementations • 6 Feb 2023 • Farhad Pashakhanloo, Alexei Koulakov

Representational drift refers to over-time changes in neural activation accompanied by a stable task performance.

Continual Learning

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

no code implementations • 15 Oct 2022 • Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Koerding, Alexei Koulakov, Yann Lecun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

Neuroscience has long been an essential driver of progress in artificial intelligence (AI).

R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-making

no code implementations • NeurIPS 2020 • Sergey Shuvaev, Sarah Starosta, Duda Kvitsiani, Adam Kepecs, Alexei Koulakov

To address this question, the field of behavioral ecology has developed foraging paradigms – the model settings in which human and non-human subjects decided when to leave depleting food resources.

Decision Making Reinforcement Learning (RL)