3 papers
cs.LG2025
Benchmarking Probabilistic Time Series Forecasting Models on Neural Activity
Ziyu Lu, Anna J. Li, Alexander E. Ladd +5
Neural activity forecasting is central to understanding neural systems and enabling closed-loop control. While deep learning has recently advanced the state-of-the-art in the time…
cs.LG2025
Interpretable time series analysis with Gumbel dynamics
Yiliu Wang, Timothy Doyeon Kim, Eric Shea-Brown +1
Switching dynamical systems can model complicated time series data while maintaining interpretability by inferring a finite set of dynamics primitives and explaining different port…
cs.LG2023
Attention for Causal Relationship Discovery from Biological Neural Dynamics
Ziyu Lu, Anika Tabassum, Shruti Kulkarni +4
This paper explores the potential of the transformer models for learning Granger causality in networks with complex nonlinear dynamics at every node, as in neurobiological and biop…