Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks

11 October 2021

Papers citing "Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks"

7 / 7 papers shown

Title
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness Boqian Wu Q. Xiao Shunxin Wang N. Strisciuglio Mykola Pechenizkiy M. V. Keulen D. Mocanu Elena Mocanu OOD 3DH 52 0 0 03 Oct 2024
FOCIL: Finetune-and-Freeze for Online Class Incremental Learning by Training Randomly Pruned Sparse Experts Murat Onur Yildirim Elif Ceren Gok Yildirim D. Mocanu Joaquin Vanschoren CLL 36 0 0 13 Mar 2024
Continual learning for surface defect segmentation by subnetwork creation and selection Aleksandr Dekhovich Miguel A. Bessa CLL 18 3 0 08 Dec 2023
Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates Murat Onur Yildirim Elif Ceren Gok Yildirim Ghada Sokar D. Mocanu Joaquin Vanschoren CLL 20 7 0 28 Aug 2023
iPINNs: Incremental learning for Physics-informed neural networks Aleksandr Dekhovich M. Sluiter David Tax Miguel A. Bessa AI4CE DiffM 12 10 0 10 Apr 2023
Architecture Matters in Continual Learning Seyed Iman Mirzadeh Arslan Chaudhry Dong Yin Timothy Nguyen Razvan Pascanu Dilan Görür Mehrdad Farajtabar OOD KELM 109 58 0 01 Feb 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 139 684 0 31 Jan 2021