Overview

This workshop will explore the intersection of probabilistic inference and neuroscience, highlighting approaches for extracting probabilistic models from ever-larger neural datasets and for understanding how the brain itself does inference. The workshop will explore themes including: Learning of internal models of the environment;  Decision-making from inferred probabilities; Probabilistic model inference using neurons; Information bottleneck in neurons; Stochastic dynamics in neural computation; Unsupervised learning; and Fitting probabilistic models to large-scale neural recordings. The workshop program will include invited talks, focused discussions, and informal exchange seeking to develop unifying frameworks of probabilistic inference within neuroscience.