Search Results for author:
Found 5 papers, 1 papers with code
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Many, if not most, systems of interest in science are naturally described as nonlinear dynamical systems.
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Here we propose a general framework for multi-modal data integration for the purpose of nonlinear DS reconstruction and the analysis of cross-modal relations.
Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies
A main theoretical interest in biology and physics is to identify the nonlinear dynamical system (DS) that generated observed time series.
Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization
Vanilla RNN with ReLU activation have a simple structure that is amenable to systematic dynamical systems analysis and interpretation, but they suffer from the exploding vs. vanishing gradients problem.
Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI
A major tenet in theoretical neuroscience is that cognitive and behavioral processes are ultimately implemented in terms of the neural system dynamics.
