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Overcoming catastrophic forgetting in neural networks
v1v2 (latest)

Overcoming catastrophic forgetting in neural networks

2 December 2016
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
Andrei A. Rusu
Kieran Milan
John Quan
Tiago Ramalho
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
    CLL
ArXiv (abs)PDFHTML

Papers citing "Overcoming catastrophic forgetting in neural networks"

50 / 3,800 papers shown
Title
Residual Continual Learning
Residual Continual Learning
Janghyeon Lee
Donggyu Joo
H. Hong
Junmo Kim
CLL
140
24
0
17 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and
  Lifelong Learning
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning
Yeming Wen
Dustin Tran
Jimmy Ba
OODFedMLUQCV
275
494
0
17 Feb 2020
Regularizing activations in neural networks via distribution matching
  with the Wasserstein metric
Regularizing activations in neural networks via distribution matching with the Wasserstein metric
Taejong Joo
Donggu Kang
Byunghoon Kim
78
8
0
13 Feb 2020
Multi-Task Incremental Learning for Object Detection
Multi-Task Incremental Learning for Object Detection
Xialei Liu
Hao Yang
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
ObjDVLMCLL
71
12
0
13 Feb 2020
Salvaging Federated Learning by Local Adaptation
Salvaging Federated Learning by Local Adaptation
Tao Yu
Eugene Bagdasaryan
Vitaly Shmatikov
FedML
121
271
0
12 Feb 2020
Machine Learning Approaches For Motor Learning: A Short Review
Machine Learning Approaches For Motor Learning: A Short Review
Baptiste Caramiaux
Jules Françoise
A. Liu
Téo Sanchez
Frédéric Bevilacqua
57
11
0
11 Feb 2020
Incremental Meta-Learning via Indirect Discriminant Alignment
Incremental Meta-Learning via Indirect Discriminant Alignment
Qing Liu
Orchid Majumder
Alessandro Achille
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
CLL
55
6
0
11 Feb 2020
K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
Ruize Wang
Duyu Tang
Nan Duan
Zhongyu Wei
Xuanjing Huang
Jianshu Ji
Guihong Cao
Daxin Jiang
Ming Zhou
KELM
189
557
0
05 Feb 2020
Modeling the Background for Incremental Learning in Semantic
  Segmentation
Modeling the Background for Incremental Learning in Semantic Segmentation
Fabio Cermelli
Massimiliano Mancini
Samuel Rota Buló
Elisa Ricci
Barbara Caputo
CLLVLM
105
287
0
03 Feb 2020
Adversarial Incremental Learning
Ankur Singh
CLL
42
1
0
30 Jan 2020
Uncertainty-based Modulation for Lifelong Learning
Uncertainty-based Modulation for Lifelong Learning
Andrew P. Brna
Ryan C. Brown
P. Connolly
Stephen B. Simons
R. E. Shimizu
Mario Aguilar-Simon
54
18
0
27 Jan 2020
Ternary Feature Masks: zero-forgetting for task-incremental learning
Ternary Feature Masks: zero-forgetting for task-incremental learning
Marc Masana
Tinne Tuytelaars
Joost van de Weijer
CLL
91
30
0
23 Jan 2020
Rethinking the Distribution Gap of Person Re-identification with
  Camera-based Batch Normalization
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization
Zijie Zhuang
Longhui Wei
Lingxi Xie
Tianyu Zhang
Hengheng Zhang
Haozhe Wu
H. Ai
Qi Tian
40
1
0
23 Jan 2020
SPACE: Structured Compression and Sharing of Representational Space for
  Continual Learning
SPACE: Structured Compression and Sharing of Representational Space for Continual Learning
Gobinda Saha
Isha Garg
Aayush Ankit
Kaushik Roy
CLL
70
22
0
23 Jan 2020
Active and Incremental Learning with Weak Supervision
Active and Incremental Learning with Weak Supervision
C. Brust
Christoph Käding
Joachim Denzler
CLL
58
18
0
20 Jan 2020
Continual Learning for Domain Adaptation in Chest X-ray Classification
Continual Learning for Domain Adaptation in Chest X-ray Classification
Matthias Lenga
H. Schulz
A. Saalbach
OOD
93
61
0
16 Jan 2020
Functional Error Correction for Robust Neural Networks
Functional Error Correction for Robust Neural Networks
Kunping Huang
P. Siegel
Anxiao
Anxiao Jiang
31
26
0
12 Jan 2020
Learning credit assignment
Learning credit assignment
Chan Li
Haiping Huang
69
7
0
10 Jan 2020
Frosting Weights for Better Continual Training
Frosting Weights for Better Continual Training
Xiaofeng Zhu
Feng Liu
Goce Trajcevski
Dingding Wang
FedMLAI4CECLL
57
5
0
07 Jan 2020
How neural networks find generalizable solutions: Self-tuned annealing
  in deep learning
How neural networks find generalizable solutions: Self-tuned annealing in deep learning
Yu Feng
Y. Tu
MLT
62
9
0
06 Jan 2020
Exploring Benefits of Transfer Learning in Neural Machine Translation
Exploring Benefits of Transfer Learning in Neural Machine Translation
Tom Kocmi
71
17
0
06 Jan 2020
Dissecting Catastrophic Forgetting in Continual Learning by Deep
  Visualization
Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization
Giang Nguyen
Shuan Chen
T. Do
Tae Joon Jun
Ho-Jin Choi
Daeyoung Kim
85
10
0
06 Jan 2020
Think Locally, Act Globally: Federated Learning with Local and Global
  Representations
Think Locally, Act Globally: Federated Learning with Local and Global Representations
Paul Pu Liang
Terrance Liu
Liu Ziyin
Nicholas B. Allen
Randy P. Auerbach
David Brent
Ruslan Salakhutdinov
Louis-Philippe Morency
FedML
147
570
0
06 Jan 2020
Human Action Recognition and Assessment via Deep Neural Network
  Self-Organization
Human Action Recognition and Assessment via Deep Neural Network Self-Organization
G. I. Parisi
44
8
0
04 Jan 2020
A Neural Dirichlet Process Mixture Model for Task-Free Continual
  Learning
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
Soochan Lee
Junsoo Ha
Dongsu Zhang
Gunhee Kim
BDLCLL
116
212
0
03 Jan 2020
Side-Tuning: A Baseline for Network Adaptation via Additive Side
  Networks
Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks
Jeffrey O. Zhang
Alexander Sax
Amir Zamir
Leonidas Guibas
Jitendra Malik
98
28
0
31 Dec 2019
Questions to Guide the Future of Artificial Intelligence Research
Questions to Guide the Future of Artificial Intelligence Research
J. Ott
32
3
0
21 Dec 2019
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural
  Pruning and Synaptic Consolidation
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation
Jian-wei Peng
Bo Tang
Jiang Hao
Zhuo Li
Yinjie Lei
Tao R. Lin
Haifeng Li
AAMLCLL
77
38
0
19 Dec 2019
Continuous Meta-Learning without Tasks
Continuous Meta-Learning without Tasks
James Harrison
Apoorva Sharma
Chelsea Finn
Marco Pavone
CLLOOD
98
79
0
18 Dec 2019
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
Hongxu Yin
Pavlo Molchanov
Zhizhong Li
J. Álvarez
Arun Mallya
Derek Hoiem
N. Jha
Jan Kautz
193
571
0
18 Dec 2019
A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics
A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics
Aiqing Fang
Xinbo Zhao
Jiaqi Yang
Yanning Zhang
52
6
0
18 Dec 2019
Direction Concentration Learning: Enhancing Congruency in Machine
  Learning
Direction Concentration Learning: Enhancing Congruency in Machine Learning
Yan Luo
Yongkang Wong
Mohan Kankanhalli
Qi Zhao
68
12
0
17 Dec 2019
Personalization of End-to-end Speech Recognition On Mobile Devices For
  Named Entities
Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entities
K. Sim
F. Beaufays
Arnaud Benard
Dhruv Guliani
Andreas Kabel
...
P. Zadrazil
Harry Zhang
Leif T. Johnson
Giovanni Motta
Lillian Zhou
97
84
0
14 Dec 2019
L3DOC: Lifelong 3D Object Classification
L3DOC: Lifelong 3D Object Classification
Yuyang Liu
Yang Cong
Gan Sun
3DPC
52
2
0
12 Dec 2019
How to Evaluate the Next System: Automatic Dialogue Evaluation from the
  Perspective of Continual Learning
How to Evaluate the Next System: Automatic Dialogue Evaluation from the Perspective of Continual Learning
Lu Li
Zhongheng He
Xiangyang Zhou
Dianhai Yu
63
3
0
10 Dec 2019
Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic
  Information Balancing
Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing
Mohammed Amer
Tomás Maul
49
6
0
10 Dec 2019
Bayesian Structure Adaptation for Continual Learning
Bayesian Structure Adaptation for Continual Learning
Abhishek Kumar
Sunabha Chatterjee
Piyush Rai
CLLBDL
66
30
0
08 Dec 2019
Regularization Shortcomings for Continual Learning
Regularization Shortcomings for Continual Learning
Timothée Lesort
Andrei Stoian
David Filliat
CLL
107
50
0
06 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual
  Learning
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning
Samuel Kessler
Vu Nguyen
S. Zohren
Stephen J. Roberts
BDL
102
25
0
04 Dec 2019
Neural Machine Translation: A Review and Survey
Neural Machine Translation: A Review and Survey
Felix Stahlberg
3DVAI4TSMedIm
155
332
0
04 Dec 2019
Learning to Recommend via Meta Parameter Partition
Learning to Recommend via Meta Parameter Partition
Liang Zhao
Yang Wang
Daxiang Dong
Hao Tian
OffRLCLL
90
7
0
04 Dec 2019
Overcoming Catastrophic Forgetting by Generative Regularization
Overcoming Catastrophic Forgetting by Generative Regularization
Peiqiu Chen
Wei Wei
Cho-Jui Hsieh
Bo Dai
CLL
64
17
0
03 Dec 2019
Adaptive Online Planning for Continual Lifelong Learning
Adaptive Online Planning for Continual Lifelong Learning
Kevin Lu
Igor Mordatch
Pieter Abbeel
OffRLOnRLCLL
97
15
0
03 Dec 2019
Latent Replay for Real-Time Continual Learning
Latent Replay for Real-Time Continual Learning
Lorenzo Pellegrini
G. Graffieti
Vincenzo Lomonaco
Davide Maltoni
CLL
131
167
0
02 Dec 2019
Continuous Adaptation for Interactive Object Segmentation by Learning
  from Corrections
Continuous Adaptation for Interactive Object Segmentation by Learning from Corrections
Theodora Kontogianni
Michael Gygli
J. Uijlings
V. Ferrari
CLLVLM
109
59
0
28 Nov 2019
GRIm-RePR: Prioritising Generating Important Features for
  Pseudo-Rehearsal
GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal
C. Atkinson
B. McCane
Lech Szymanski
Anthony Robins
49
0
0
27 Nov 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with
  Robustness to Domain Shift
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift
A. Mozafari
H. Gomes
Christian Gagné
32
0
0
25 Nov 2019
A Conceptual Framework for Lifelong Learning
A Conceptual Framework for Lifelong Learning
Charles X. Ling
Tanner A. Bohn
CLL
104
3
0
21 Nov 2019
Continual Learning with Adaptive Weights (CLAW)
Continual Learning with Adaptive Weights (CLAW)
T. Adel
Han Zhao
Richard Turner
CLL
76
73
0
21 Nov 2019
Learning to Control Latent Representations for Few-Shot Learning of
  Named Entities
Learning to Control Latent Representations for Few-Shot Learning of Named Entities
Omar U. Florez
Erik T. Mueller
BDL
96
5
0
19 Nov 2019
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