13 citations · 21 across the 11 of their papers we have counts for
4 papers · 1 filter
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics
Yenho Chen, Noga Mudrik, Kyle A. Johnsen +3
Time-varying linear state-space models are powerful tools for obtaining mathematically interpretable representations of neural signals. For example, switching and decomposed models…
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
Jiancheng Xie, Lou C. Kohler Voinov, Noga Mudrik +2
Recurrent neural networks (RNNs) are a widely used tool for sequential data analysis; however, they are still often seen as black boxes. Visualizing the internal dynamics of RNNs i…
CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations
Noga Mudrik, Ryan Ly, Oliver Ruebel +1
Modern recordings of neural activity provide diverse observations of neurons across brain areas, conditions, and subjects; presenting an exciting opportunity to reveal the fundamen…
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability
Noga Mudrik, Eva Yezerets, Yenho Chen +2
Identifying latent interactions within complex systems is key to unlocking deeper insights into their operational dynamics, including how their elements affect each other and contr…