(1/n) Presenting our NeurIPS’25 work at #cosyne2026 poster 3-109
We introduce a flexible framework to infer how animals learn new decision-making tasks from scratch without assuming REINFORCE/Q-learning.
Paper: arxiv.org/abs/2509.04661
Joint w/ @vgeadah.bsky.social and @jpillowtime.bsky.social
arxiv.org
Flexible inference for animal learning rules using neural networks
Understanding how animals learn is a central challenge in neuroscience, with growing relevance to the development of animal- or human-aligned artificial intelligence. However, existing approaches tend...