Optimizing Neural Networks via Koopman Operator Theory

3 June 2020

Papers citing "Optimizing Neural Networks via Koopman Operator Theory"

10 / 10 papers shown

Title
Iterative Magnitude Pruning as a Renormalisation Group: A Study in The Context of The Lottery Ticket Hypothesis Abu-Al Hassan 33 0 0 06 Aug 2023
Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing King Fai Yeh Paris D. L. Flood William T. Redman Pietro Lio 30 1 0 15 May 2023
Koopman-based generalization bound: New aspect for full-rank weights Yuka Hashimoto Sho Sonoda Isao Ishikawa Atsushi Nitanda Taiji Suzuki 11 2 0 12 Feb 2023
Enhancing Neural Network Differential Equation Solvers Matthew J. H. Wright 21 0 0 28 Dec 2022
The Underlying Correlated Dynamics in Neural Training Rotem Turjeman Tom Berkov I. Cohen Guy Gilboa 27 3 0 18 Dec 2022
Learning to Optimize with Dynamic Mode Decomposition Petr Simánek Daniel Vasata Pavel Kordík 31 5 0 29 Nov 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 19 11 0 16 Aug 2022
Stable Invariant Models via Koopman Spectra Takuya Konishi Yoshinobu Kawahara 23 3 0 15 Jul 2022
Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics Chunheng Jiang Tejaswini Pedapati Pin-Yu Chen Yizhou Sun Jianxi Gao 24 2 0 11 Jan 2022
Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems Giorgos Mamakoukas Maria L. Castaño Xiaobo Tan Todd D. Murphey 18 92 0 12 Oct 2020