Sequential mastery of multiple visual tasks: Networks naturally learn to learn and forget to forget

26 May 2019

Papers citing "Sequential mastery of multiple visual tasks: Networks naturally learn to learn and forget to forget"

8 / 8 papers shown

Title
Bridging Neuroscience and AI: Environmental Enrichment as a Model for Forward Knowledge Transfer Rajat Saxena Bruce L. McNaughton CLL 53 2 0 12 May 2024
RMM: Reinforced Memory Management for Class-Incremental Learning Yaoyao Liu Bernt Schiele Qianru Sun CLL 21 92 0 14 Jan 2023
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 50 102 0 30 Jun 2022
Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation Chenyu You Jinlin Xiang Kun Su Xiaoran Zhang Siyuan Dong J. Onofrey Lawrence H. Staib James S. Duncan CLL 20 51 0 03 Jun 2022
Replay in Deep Learning: Current Approaches and Missing Biological Elements Tyler L. Hayes G. Krishnan M. Bazhenov H. Siegelmann T. Sejnowski Christopher Kanan CLL 31 129 0 01 Apr 2021
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types Thomas Mensink J. Uijlings Alina Kuznetsova Michael Gygli V. Ferrari VLM 32 80 0 24 Mar 2021
Adaptive Aggregation Networks for Class-Incremental Learning Yaoyao Liu Bernt Schiele Qianru Sun CLL 13 215 0 10 Oct 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 314 11,681 0 09 Mar 2017