A study on the plasticity of neural networks

A study on the plasticity of neural networks

31 May 2021

Wojciech M. Czarnecki

Samuel L. Smith

Claudia Clopath

Papers citing "A study on the plasticity of neural networks"

9 / 9 papers shown

Title
Breaking the Reclustering Barrier in Centroid-based Deep Clustering Lukas Miklautz Timo Klein Kevin Sidak Collin Leiber Thomas Lang Andrii Shkabrii Sebastian Tschiatschek Claudia Plant 34 1 0 04 Nov 2024
Neuroplastic Expansion in Deep Reinforcement Learning Jiashun Liu J. Obando-Ceron Rameswar Panda L. Pan 42 3 0 10 Oct 2024
Normalization and effective learning rates in reinforcement learning Clare Lyle Zeyu Zheng Khimya Khetarpal James Martens H. V. Hasselt Razvan Pascanu Will Dabney 19 7 0 01 Jul 2024
Directions of Curvature as an Explanation for Loss of Plasticity Alex Lewandowski Haruto Tanaka Dale Schuurmans Marlos C. Machado 19 5 0 30 Nov 2023
Continual Learning: Applications and the Road Forward Eli Verwimp Rahaf Aljundi Shai Ben-David Matthias Bethge Andrea Cossu ... Joost van de Weijer Bing Liu Vincenzo Lomonaco Tinne Tuytelaars Gido M. van de Ven CLL 43 44 0 20 Nov 2023
Understanding plasticity in neural networks Clare Lyle Zeyu Zheng Evgenii Nikishin Bernardo Avila-Pires Razvan Pascanu Will Dabney AI4CE 35 97 0 02 Mar 2023
The Dormant Neuron Phenomenon in Deep Reinforcement Learning Ghada Sokar Rishabh Agarwal Pablo Samuel Castro Utku Evci CLL 51 88 0 24 Feb 2023
Does Optimal Source Task Performance Imply Optimal Pre-training for a Target Task? Steven Gutstein Brent Lance Sanjay Shakkottai 27 1 0 21 Jun 2021
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,890 0 15 Sep 2016