Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics

15 December 2022

Papers citing "Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics"

9 / 9 papers shown

Title
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction Manuel Brenner Christoph Jurgen Hemmer Zahra Monfared Daniel Durstewitz AI4CE 35 1 0 18 Oct 2024
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data Manuel Brenner Elias Weber G. Koppe Daniel Durstewitz AI4TS AI4CE 36 3 0 07 Oct 2024
Inferring stochastic low-rank recurrent neural networks from neural data Matthijs Pals A Erdem Sağtekin Felix Pei Manuel Gloeckler Jakob H Macke 38 6 0 24 Jun 2024
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data Rabia Gondur Usama Bin Sikandar Evan Schaffer Mikio C. Aoi Stephen L. Keeley DRL 26 9 0 04 Oct 2023
Latent Neural ODEs with Sparse Bayesian Multiple Shooting V. Iakovlev Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL 30 11 0 07 Oct 2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 37 29 0 06 Jul 2022
A Systematic Exploration of Reservoir Computing for Forecasting Complex Spatiotemporal Dynamics Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 35 32 0 21 Jan 2022
On the difficulty of learning chaotic dynamics with RNNs Jonas M. Mikhaeil Zahra Monfared Daniel Durstewitz 59 51 0 14 Oct 2021
Rescuing neural spike train models from bad MLE Diego M. Arribas Yuan Zhao Il Memming Park 26 8 0 23 Oct 2020