Paper-Conference

Leveraging Dale’s Principle as an Inductive Bias in Recurrent Neural Networks

Learnable excitatory–inhibitory separation improves recurrent learning stability, continual learning, and reinforcement learning control.

Sep 27, 2026

Learning Reusable Motor Motifs for Continuous Animal Behavior Modeling

Discovering reusable motor motifs from offline behavior data and composing them into continuous, interpretable policies.

Sep 27, 2026

Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors

Recovering time-varying, history-dependent rewards from long behavioral trajectories with switching inverse reinforcement learning.

Jan 1, 2025