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06/07/2023
Generalized Teacher Forcing for Learning Chaotic Dynamics
Chaotic dynamical systems (DS) are ubiquitous in nature and society. Oft...
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12/15/2022
Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems
Many, if not most, systems of interest in science are naturally describe...
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07/06/2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems
In many scientific disciplines, we are interested in inferring the nonli...
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11/04/2021
Identifying nonlinear dynamical systems from multi-modal time series data
Empirically observed time series in physics, biology, or medicine, are c...
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10/14/2021
How to train RNNs on chaotic data?
Recurrent neural networks (RNNs) are wide-spread machine learning tools ...
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10/08/2019
Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization
Vanilla RNN with ReLU activation have a simple structure that is amenabl...
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02/19/2019
Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI
A major tenet in theoretical neuroscience is that cognitive and behavior...
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02/10/2018
Detecting Multiple Step Changes Using Adaptive Regression Splines with Application to Neural Recordings
Time series produced by dynamical systems as frequently the case in neur...
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12/23/2016
A State Space Approach for Piecewise-Linear Recurrent Neural Networks for Reconstructing Nonlinear Dynamics from Neural Measurements
The computational properties of neural systems are often thought to be i...
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07/04/2016