Bifurcations and loss jumps in RNN training

26 October 2023

Papers citing "Bifurcations and loss jumps in RNN training"

8 / 8 papers shown

Title
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data Manuel Brenner Elias Weber G. Koppe Daniel Durstewitz AI4TS AI4CE 44 4 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 43 7 0 24 Jun 2024
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction Christoph Jürgen Hemmer Manuel Brenner Florian Hess Daniel Durstewitz 38 4 0 07 Jun 2024
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics Manuela Brenner Florian Hess G. Koppe Daniel Durstewitz 33 10 0 15 Dec 2022
Understanding Edge-of-Stability Training Dynamics with a Minimalist Example Xingyu Zhu Zixuan Wang Xiang Wang Mo Zhou Rong Ge 69 35 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 42 30 0 06 Jul 2022
Understanding Gradient Descent on Edge of Stability in Deep Learning Sanjeev Arora Zhiyuan Li A. Panigrahi MLT 83 91 0 19 May 2022
On the difficulty of learning chaotic dynamics with RNNs Jonas M. Mikhaeil Zahra Monfared Daniel Durstewitz 64 53 0 14 Oct 2021