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continual-learning-papers
Continual Learning papers list, curated by ContinualAI
https://github.com/ContinualAI/continual-learning-papers
- Zotero group
- ContinualAI Slack
- Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting Data
- The Traffic Flow Prediction Method Using the Incremental Learning-Based CNN-LTSM Model: The Solution of Mobile Application
- Findings of the First Shared Task on Lifelong Learning Machine Translation - jussà, Fethi Bougares and Olivier Galibert. *Proceedings of the Fifth Conference on Machine Translation*, 56--64, 2020. [framework] [nlp]
- Continual Learning of Predictive Models in Video Sequences via Variational Autoencoders
- Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem - -14460, 2020. [framework] [mnist] [vision]
- Incremental Learning for End-to-End Automatic Speech Recognition
- Neural Topic Modeling with Continual Lifelong Learning
- CLOPS: Continual Learning of Physiological Signals
- Clinical Applications of Continual Learning Machine Learning - -e281, 2020.
- Continual Learning for Domain Adaptation in Chest X-ray Classification - -11, 2020. [vision]
- Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis
- RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning - -16748, 2020. [nlp]
- Importance Driven Continual Learning for Segmentation Across Domains - Marie Rickmann, Abhijit Guha Roy and Christian Wachinger. *arXiv*, 1--10, 2020. [vision]
- LAMOL: LAnguage MOdeling for Lifelong Language Learning - Keng Sun, Cheng-Hao Ho and Hung-Yi Lee. *ICLR*, 2020. [nlp]
- Non-Parametric Adaptation for Neural Machine Translation
- Episodic Memory in Lifelong Language Learning
- Continual Adaptation for Efficient Machine Communication
- Continual Learning for Sentence Representations Using Conceptors
- Lifelong and Interactive Learning of Factual Knowledge in Dialogues - -31, 2019. [nlp]
- Making Good on LSTMs' Unfulfilled Promise
- Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation - -2068, 2019. [nlp] [rnn]
- Lifelong Learning for Scene Recognition in Remote Sensing Images - -1476, 2019. [vision]
- Towards Continual Learning in Medical Imaging - -4, 2018. [vision]
- Toward Continual Learning for Conversational Agents
- Toward an Architecture for Never-Ending Language Learning - Fourth AAAI Conference on Artificial Intelligence*, 1306--1313, 2010. [nlp]
- Principles of Lifelong Learning for Predictive User Modeling - -46, 2009.
- Provable and Efficient Continual Representation Learning
- Architecture Matters in Continual Learning
- The Multiple Subnetwork Hypothesis: Enabling Multidomain Learning by Isolating Task-Specific Subnetworks in Feedforward Neural Networks
- Continual Learning with Node-Importance Based Adaptive Group Sparse Regularization
- Structured Ensembles: An Approach to Reduce the Memory Footprint of Ensemble Methods - -418, 2021.
- Continual Learning via Bit-Level Information Preserving - -16683, 2021.
- SpaceNet: Make Free Space for Continual Learning - -11, 2021. [cifar] [fashion] [mnist] [sparsity]
- Modular Dynamic Neural Network: A Continual Learning Architecture
- Continual Learning with Adaptive Weights (CLAW)
- Continual Learning with Gated Incremental Memories for Sequential Data Processing
- Continual Learning in Recurrent Neural Networks
- Explainability in Deep Reinforcement Learning - Rodr\ǵuez. *arXiv:2008.06693 [cs]*, 2020.
- A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
- Bayesian Nonparametric Weight Factorization for Continual Learning - -17, 2020. [bayes] [cifar] [mnist] [sparsity]
- Efficient Continual Learning with Modular Networks and Task-Driven Priors
- Progressive Memory Banks for Incremental Domain Adaptation
- Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments - -674, 2019. [mnist]
- Compacting, Picking and Growing for Unforgetting Continual Learning - Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan and Chu-Song Chen. *NeurIPS*, 13669--13679, 2019. [cifar] [imagenet]
- Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
- Towards AutoML in the Presence of Drift: First Results - Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon and Michele Sebag. *arXiv*, 2019.
- Continual Unsupervised Representation Learning
- A Progressive Model to Enable Continual Learning for Semantic Slot Filling - -1284, 2019. [nlp]
- Adaptive Compression-based Lifelong Learning
- Frosting Weights for Better Continual Training - -510, 2019. [cifar] [mnist]
- Dynamic Few-Shot Visual Learning Without Forgetting - -4375, 2018. [imagenet] [vision]
- HOUDINI: Lifelong Learning as Program Synthesis - -8698, 2018.
- Reinforced Continual Learning - -908, 2018. [cifar] [mnist]
- Lifelong Learning With Dynamically Expandable Networks
- Expert Gate: Lifelong Learning with a Network of Experts
- Neurogenesis Deep Learning
- Net2Net: Accelerating Learning via Knowledge Transfer
- Continual Learning through Evolvable Neural Turing Machines
- Progressive Neural Networks
- Knowledge Transfer in Deep Block-Modular Neural Networks - -279, 2015. [vision]
- ELLA: An Efficient Lifelong Learning Algorithm - -515, 2013.
- A Self-Organising Network That Grows When Required - -1058, 2002. [som]
- vCLIMB: A Novel Video Class Incremental Learning Benchmark
- Is Class-Incremental Enough for Continual Learning?
- A Procedural World Generation Framework for Systematic Evaluation of Continual Learning - Fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track*, 2021.
- Efficient Continual Learning with Modular Networks and Task-Driven Priors
- Defining Benchmarks for Continual Few-Shot Learning
- Evaluating Online Continual Learning with CALM - Teodor Sorodoc and Tomas Mikolov. *arXiv*, 2020. [nlp] [rnn]
- Continual Reinforcement Learning in 3D Non-Stationary Environments - -249, 2020.
- Stream-51: Streaming Classification and Novelty Detection From Videos - -229, 2020.
- OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning - -8, 2019. [vision]
- Incremental Object Learning From Contiguous Views - -8786, 2019.
- New Metrics and Experimental Paradigms for Continual Learning - -21123, 2018.
- CORe50: A New Dataset and Benchmark for Continuous Object Recognition - -26, 2017. [vision]
- lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents
- SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic Environments
- A Biologically Plausible Audio-Visual Integration Model for Continual Learning
- Synaptic Metaplasticity in Binarized Neural Networks
- Controlled Forgetting: Targeted Stimulation and Dopaminergic Plasticity Modulation for Unsupervised Lifelong Learning in Spiking Neural Networks
- Storing Encoded Episodes as Concepts for Continual Learning
- Cognitively-Inspired Model for Incremental Learning Using a Few Examples
- Spiking Neural Predictive Coding for Continual Learning from Data Streams
- Brain-like Replay for Continual Learning with Artificial Neural Networks
- Selfless Sequential Learning
- Backpropamine: Training Self-Modifying Neural Networks with Differentiable Neuromodulated Plasticity
- Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations
- Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting When Learning Cumulatively - -11, 2019. [fashion] [mnist] [sparsity]
- FearNet: Brain-Inspired Model for Incremental Learning
- Differentiable Plasticity: Training Plastic Neural Networks with Backpropagation - -3568, 2018.
- Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization
- SLAYER: Spike Layer Error Reassignment in Time - -1421, 2018.
- Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World - -1702, 2017. [nlp] [vision]
- Diffusion-Based Neuromodulation Can Eliminate Catastrophic Forgetting in Simple Neural Networks - -31, 2017.
- How Do Neurons Operate on Sparse Distributed Representations? A Mathematical Theory of Sparsity, Neurons and Active Dendrites - -23, 2016. [hebbian] [sparsity]
- Continuous Online Sequence Learning with an Unsupervised Neural Network Model - -2504, 2016. [spiking]
- Backpropagation of Hebbian Plasticity for Continual Learning - Continual Learning*, 5, 2016.
- Mitigation of Catastrophic Forgetting in Recurrent Neural Networks Using a Fixed Expansion Layer - -7, 2013. [mnist] [rnn] [sparsity]
- Compete to Compute
- Mitigation of Catastrophic Interference in Neural Networks Using a Fixed Expansion Layer - -729, 2012. [sparsity]
- Synaptic Plasticity: Taming the Beast - -1183, 2000. [hebbian]
- Architecture Matters in Continual Learning
- Continual Learning in the Teacher-Student Setup: Impact of Task Similarity - -6119, 2021.
- Continual Learning in Deep Networks: An Analysis of the Last Layer
- Understanding Continual Learning Settings with Data Distribution Drift Analysis
- Wide Neural Networks Forget Less Catastrophically
- Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics
- Does Continual Learning = Catastrophic Forgetting?
- Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to Forget - -9293, 2020. [vision]
- Understanding the Role of Training Regimes in Continual Learning
- Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization - Jin Choi and Daeyoung Kim. *arXiv*, 2020. [vision]
- Toward Understanding Catastrophic Forgetting in Continual Learning
- A Study on Catastrophic Forgetting in Deep LSTM Networks - -728, 2019. [rnn]
- An Empirical Study of Example Forgetting during Deep Neural Network Learning
- Localizing Catastrophic Forgetting in Neural Networks
- An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
- The Stability-Plasticity Dilemma: Investigating the Continuum from Catastrophic Forgetting to Age-Limited Learning Effects
- Catastrophic Forgetting in Connectionist Networks - 2) by and Robert French. *Trends in Cognitive Sciences*, 128--135, 1999. [sparsity]
- How Does a Brain Build a Cognitive Code? - -51, 1980.
- Lifelong Machine Learning: A Paradigm for Continuous Learning - -361, 2017.
- The Organization of Behavior: A Neuropsychological Theory
- Pseudo-Recurrent Connectionist Networks: An Approach to the 'Sensitivity-Stability' Dilemma - -380, 1997. [dual]
- CHILD: A First Step Towards Continual Learning - -104, 1997.
- Is Learning The N-Th Thing Any Easier Than Learning The First? - -646, 1996. [vision]
- Learning in the Presence of Concept Drift and Hidden Contexts - -101, 1996.
- Using Semi-Distributed Representations to Overcome Catastrophic Forgetting in Connectionist Networks - -178, 1991. [sparsity]
- Connectionist Models of Recognition Memory: Constraints Imposed by Learning and Forgetting Functions - -308, 1990.
- The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network - -88, 1988.
- How Does a Brain Build a Cognitive Code? - -51, 1980.
- Few-Shot Continual Learning: A Brain-Inspired Approach
- Defining Benchmarks for Continual Few-Shot Learning
- Tell Me What This Is: Few-Shot Incremental Object Learning by a Robot
- La-MAML: Look-ahead Meta Learning for Continual Learning
- iTAML: An Incremental Task-Agnostic Meta-learning Approach - --13597, 2020. [cifar] [imagenet]
- Wandering within a World: Online Contextualized Few-Shot Learning
- Few-Shot Class-Incremental Learning
- Few-Shot Class-Incremental Learning via Feature Space Composition
- Online Fast Adaptation and Knowledge Accumulation: A New Approach to Continual Learning
- Continuous Meta-Learning without Tasks
- Task Agnostic Continual Learning via Meta Learning
- Reconciling Meta-Learning and Continual Learning with Online Mixtures of Tasks - -9133, 2019. [bayes] [vision]
- Lifetime Policy Reuse and the Importance of Task Capacity
- Unsupervised Lifelong Learning with Curricula - -3545, 2021.
- Continuous Coordination As a Realistic Scenario for Lifelong Learning - -8024, 2021.
- Reducing Catastrophic Forgetting When Evolving Neural Networks
- A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning - -5700, 2019.
- Policy Consolidation for Continual Reinforcement Learning
- Continual Learning Exploiting Structure of Fractal Reservoir Computing - -47, 2019. [rnn]
- Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
- Leaky Tiling Activations: A Simple Approach to Learning Sparse Representations Online
- Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
- Experience Replay for Continual Learning - -360, 2019.
- Selective Experience Replay for Lifelong Learning - Second AAAI Conference on Artificial Intelligence*, 3302--3309, 2018.
- Continual Reinforcement Learning with Complex Synapses
- Unicorn: Continual Learning with a Universal, Off-policy Agent - -17, 2018.
- Lifelong Inverse Reinforcement Learning - -4513, 2018.
- Progress & Compress: A Scalable Framework for Continual Learning - Barwinska, Yee Whye Teh, Razvan Pascanu and Raia Hadsell. *International Conference on Machine Learning*, 4528--4537, 2018. [vision]
- Overcoming Catastrophic Forgetting in Neural Networks - Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran and Raia Hadsell. *PNAS*, 3521--3526, 2017. [mnist]
- Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory - -901, 2017.
- Stable Predictive Representations with General Value Functions for Continual Learning
- Continual Learning through Evolvable Neural Turing Machines
- Progressive Neural Networks
- Lifelong-RL: Lifelong Relaxation Labeling for Separating Entities and Aspects in Opinion Targets. - -235, 2016. [nlp]
- CHILD: A First Step Towards Continual Learning - -104, 1997.
- Continual Sequence Generation with Adaptive Compositional Modules
- Continual Learning for Recurrent Neural Networks: An Empirical Evaluation - -627, 2021. [rnn]
- Continual Competitive Memory: A Neural System for Online Task-Free Lifelong Learning
- Continual Learning with Gated Incremental Memories for Sequential Data Processing
- Organizing Recurrent Network Dynamics by Task-Computation to Enable Continual Learning
- Meta-Consolidation for Continual Learning
- Compositional Language Continual Learning
- Online Continual Learning on Sequences
- Unsupervised Progressive Learning and the STAM Architecture
- Toward Training Recurrent Neural Networks for Lifelong Learning - -35, 2019. [rnn]
- Semi-Supervised Tuning from Temporal Coherence - -2514, 2016.
- Self-Refreshing Memory in Artificial Neural Networks: Learning Temporal Sequences without Catastrophic Forgetting - -99, 2004. [rnn]
- Using Pseudo-Recurrent Connectionist Networks to Solve the Problem of Sequential Learning
- Knowledge Uncertainty and Lifelong Learning in Neural Systems
- An Introduction to Lifelong Supervised Learning
- Large-Scale Deep Class-Incremental Learning. (Apprentissage Incrémental Profond à Large ̧́helle)
- Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes
- Open Set Classification for Deep Learning in Large-Scale and Continual Learning Models
- Continual Learning in Neural Networks
- Continual Deep Learning via Progressive Learning
- Continual Learning with Deep Architectures
- Explanation-Based Neural Network Learning: A Lifelong Learning Approach
- Continual Learning in Reinforcement Environments
- Foundational Models for Continual Learning: An Empirical Study of Latent Replay
- Brain-Inspired Replay for Continual Learning with Artificial Neural Networks
- Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
- Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay
- Continual Learning of New Sound Classes Using Generative Replay
- Generative Replay with Feedback Connections as a General Strategy for Continual Learning
- Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory - -901, 2017.
- Continual Learning with Deep Generative Replay - -2999, 2017. [mnist]
- Dark Experience for General Continual Learning: A Strong, Simple Baseline - -15930, 2020.
- Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches - -247, 2020. [core50]
- Linear Mode Connectivity in Multitask and Continual Learning
- Efficient Continual Learning in Neural Networks with Embedding Regularization - -148, 2020.
- Efficient Lifelong Learning with A-GEM
- Single-Net Continual Learning with Progressive Segmented Training (PST) - -1636, 2019. [cifar]
- Continuous Learning in Single-Incremental-Task Scenarios - -73, 2019. [core50] [framework]
- Toward Training Recurrent Neural Networks for Lifelong Learning - -35, 2019. [rnn]
- Continual Learning of New Sound Classes Using Generative Replay
- Lifelong Learning via Progressive Distillation and Retrospection
- Progress & Compress: A Scalable Framework for Continual Learning - Barwinska, Yee Whye Teh, Razvan Pascanu and Raia Hadsell. *International Conference on Machine Learning*, 4528--4537, 2018. [vision]
- Gradient Episodic Memory for Continual Learning - Paz and Marc'Aurelio Ranzato. *NIPS*, 2017. [cifar] [mnist]
- Learning to Continually Learn
- Continual Learning with Deep Artificial Neurons
- Meta-Consolidation for Continual Learning
- Meta Continual Learning via Dynamic Programming
- Online Meta-Learning
- Task Agnostic Continual Learning via Meta Learning
- Meta-Learning Representations for Continual Learning
- Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
- Meta Continual Learning - Yeon Cho, Daejoong Kim and Jiwon Kim. *arXiv*, 2018. [mnist]
- Continual Learning in Deep Networks: An Analysis of the Last Layer
- Avalanche: An End-to-End Library for Continual Learning
- CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability
- Online Fast Adaptation and Knowledge Accumulation: A New Approach to Continual Learning
- Optimal Continual Learning Has Perfect Memory and Is NP-HARD
- Regularization Shortcomings for Continual Learning
- Strategies for Improving Single-Head Continual Learning Performance - -460, 2019. [cifar] [mnist]
- Towards Robust Evaluations of Continual Learning
- Don't Forget, There Is More than Forgetting: New Metrics for Continual Learning - Rodr\ǵuez, Vincenzo Lomonaco, David Filliat and Davide Maltoni. *arXiv*, 2018. [cifar] [framework]
- Three Scenarios for Continual Learning
- Biological Underpinnings for Lifelong Learning Machines - Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero-Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou and Hava Siegelmann. *Nature Machine Intelligence*, 196--210, 2022.
- Neural Inhibition for Continual Learning and Memory - -94, 2021.
- Can Sleep Protect Memories from Catastrophic Forgetting?
- Synaptic Consolidation: An Approach to Long-Term Learning - -257, 2012. [hebbian]
- The Organization of Behavior: A Neuropsychological Theory
- Negative Transfer Errors in Sequential Cognitive Skills: Strong-but-wrong Sequence Application. - -625, 2000.
- Connectionist Models of Recognition Memory: Constraints Imposed by Learning and Forgetting Functions. - -308, 1990.
- Dataset Knowledge Transfer for Class-Incremental Learning without Memory - 8, 2022*, 3311--3320, 2022.
- Continual Novelty Detection
- Co\$2̂\$L: Contrastive Continual Learning
- Sustainable Artificial Intelligence through Continual Learning
- Continual Backprop: Stochastic Gradient Descent with Persistent Randomness
- Continuum: Simple Management of Complex Continual Learning Scenarios
- Posterior Meta-Replay for Continual Learning
- Rethinking the Representational Continuity: Towards Unsupervised Continual Learning
- Representation Memorization for Fast Learning New Knowledge without Forgetting
- Neural Architecture Search of Deep Priors: Towards Continual Learning Without Catastrophic Interference - -3532, 2021.
- Active Class Incremental Learning for Imbalanced Datasets - ECCV 2020 Workshops - Glasgow, UK, August 23-28, 2020, Proceedings, Part VI*, 146--162, 2020.
- Initial Classifier Weights Replay for Memoryless Class Incremental Learning - 10, 2020*, 2020.
- Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
- Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis - -15, 2020. [core50] [imagenet]
- Continual Learning with Bayesian Neural Networks for Non-Stationary Data
- Energy-Based Models for Continual Learning
- Continual Learning Using Task Conditional Neural Networks
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting - An Liu, Yuting Su, Bernt Schiele and Qianru Sun. *arXiv*, 2020. [cifar] [imagenet]
- Continual Universal Object Detection
- Gradient Projection Memory for Continual Learning
- Structured Compression and Sharing of Representational Space for Continual Learning
- Gated Linear Networks - Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt and Marcus Hutter. *arXiv*, 2020.
- Lifelong Graph Learning
- Superposition of Many Models into One
- Continual Learning in Practice
- Dynamically Constraining Connectionist Networks to Produce Distributed, Orthogonal Representations to Reduce Catastrophic Interference - -340, 2019.
- Continual Learning via Neural Pruning
- BooVAE: A Scalable Framework for Continual VAE Learning under Boosting Approach
- Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild - -321, 2019.
- Continual Learning Using Bayesian Neural Networks
- Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
- Continual Rare-Class Recognition with Emerging Novel Subclasses
- Random Path Selection for Incremental Learning - -12679, 2019. [cifar] [imagenet] [mnist]
- Improving and Understanding Variational Continual Learning - -17, 2019. [bayes] [mnist]
- Continual Learning via Online Leverage Score Sampling
- Class-Incremental Learning Based on Feature Extraction of CNN With Optimized Softmax and One-Class Classifiers - -42031, 2019. [cifar] [mnist]
- Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
- DeeSIL: Deep-Shallow Incremental Learning - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part II*, 151--157, 2018.
- A Unifying Bayesian View of Continual Learning
- Overcoming Catastrophic Interference Using Conceptor-Aided Backpropagation
- Less-Forgetful Learning for Domain Expansion in Deep Neural Networks - Second AAAI Conference on Artificial Intelligence*, 2018.
- Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights - -88, 2018. [imagenet]
- Adding New Tasks to a Single Network with Weight Transformations Using Binary Masks - -189, 2018. [sparsity] [vision]
- Variational Continual Learning
- Task Agnostic Continual Learning Using Online Variational Bayes
- Encoder Based Lifelong Learning - -1337, 2017. [imagenet] [vision]
- Fine-Tuning Deep Neural Networks in Continuous Learning Scenarios
- Using Hindsight to Anchor Past Knowledge in Continual Learning - Paz. *arXiv*, 2021.
- Contrastive Continual Learning with Feature Propagation
- Gradient Projection Memory for Continual Learning
- Gradient Projection Memory for Continual Learning
- Modeling the Background for Incremental Learning in Semantic Segmentation - -9242, 2020.
- PLOP: Learning without Forgetting for Continual Semantic Segmentation
- Insights from the Future for Continual Learning
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning
- Uncertainty-Guided Continual Learning with Bayesian Neural Networks
- Continual Learning of Object Instances
- Efficient Continual Learning in Neural Networks with Embedding Regularization
- Continual Learning with Hypernetworks
- Uncertainty-Based Continual Learning with Adaptive Regularization - -4402, 2019. [bayes] [cifar] [mnist]
- Task-Free Continual Learning
- Learning without Memorizing - Chuan Peng, Ziyan Wu and Rama Chellappa. *CVPR*, 2019. [cifar]
- Incremental Learning Techniques for Semantic Segmentation - 2019 International Conference on Computer Vision Workshop, ICCVW 2019*, 3205--3212, 2019.
- Functional Regularisation for Continual Learning Using Gaussian Processes
- Memory Aware Synapses: Learning What (Not) to Forget
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence - -547, 2018.
- Rotate Your Networks: Better Weight Consolidation and Less Catastrophic Forgetting - -2268, 2018. [cifar] [mnist]
- Online Structured Laplace Approximations For Overcoming Catastrophic Forgetting
- Overcoming Catastrophic Forgetting with Hard Attention to the Task
- Overcoming Catastrophic Forgetting in Neural Networks - Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran and Raia Hadsell. *PNAS*, 3521--3526, 2017. [mnist]
- Overcoming Catastrophic Forgetting by Incremental Moment Matching - Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha and Byoung-Tak Zhang. *Advances in Neural Information Processing Systems*, 4653--4663, 2017. [bayes] [cifar] [mnist]
- Lifelong Generative Modeling - -14, 2017. [fashion] [generative] [mnist]
- Continual Learning in Generative Adversarial Nets - -9, 2017. [mnist]
- Incremental Learning of Object Detectors without Catastrophic Forgetting - -3429, 2017.
- Continual Learning Through Synaptic Intelligence - -3995, 2017. [cifar] [mnist]
- Learning without Forgetting - -629, 2016. [imagenet]
- It's All About Consistency: A Study on Memory Composition for Replay-Based Methods in Continual Learning - Saez, Vladimir Araujo, Vincenzo Lomonaco and Davide Bacciu. , 2022.
- Foundational Models for Continual Learning: An Empirical Study of Latent Replay
- Using Hindsight to Anchor Past Knowledge in Continual Learning - Paz. *arXiv*, 2021.
- Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams - -8259, 2021. [cifar] [framework] [mnist] [vision]
- Replay in Deep Learning: Current Approaches and Missing Biological Elements - -2950, 2021.
- Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay -- 3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A Continual Object Classification
- Distilled Replay: Overcoming Forgetting through Synthetic Samples - Supervised Learning (CSSL) at IJCAI*, 2021.
- Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning - -9394, 2021.
- Online Coreset Selection for Rehearsal-based Continual Learning
- CALM: Continuous Adaptive Learning for Language Modeling
- ScaIL: Classifier Weights Scaling for Class Incremental Learning - 5, 2020*, 1255--1264, 2020.
- REMIND Your Neural Network to Prevent Catastrophic Forgetting
- CLOPS: Continual Learning of Physiological Signals
- Continual Learning with Bayesian Neural Networks for Non-Stationary Data
- GDumb: A Simple Approach That Questions Our Progress in Continual Learning - -540, 2020.
- Graph-Based Continual Learning
- Brain-Inspired Replay for Continual Learning with Artificial Neural Networks
- Continual Learning with Hypernetworks
- Online Continual Learning with Maximal Interfered Retrieval - Caccia. *Advances in Neural Information Processing Systems 32*, 11849--11860, 2019. [cifar] [mnist]
- Gradient Based Sample Selection for Online Continual Learning - -11825, 2019. [cifar] [mnist]
- IL2M: Class Incremental Learning With Dual Memory - November 2, 2019*, 583--592, 2019.
- On Tiny Episodic Memories in Continual Learning
- Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients
- Memory Efficient Experience Replay for Streaming Learning
- Experience Replay for Continual Learning - -360, 2019.
- Prototype Reminding for Continual Learning - -10, 2019. [bayes] [cifar] [imagenet] [mnist]
- Selective Experience Replay for Lifelong Learning - Second AAAI Conference on Artificial Intelligence*, 3302--3309, 2018.
- iCaRL: Incremental Classifier and Representation Learning - Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl and Christoph H Lampert. *The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)*, 2017. [cifar]
- Preventing Catastrophic Interference in MultipleSequence Learning Using Coupled Reverberating Elman Networks
- A Comparative Study of Calibration Methods for Imbalanced Class Incremental Learning
- How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition
- A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks - -54, 2021.
- Continual Learning for Recurrent Neural Networks: An Empirical Evaluation - -627, 2021. [rnn]
- A Continual Learning Survey: Defying Forgetting in Classification Tasks
- Replay in Deep Learning: Current Approaches and Missing Biological Elements
- Continual Lifelong Learning in Natural Language Processing: A Survey - jussà. *Proceedings of the 28th International Conference on Computational Linguistics*, 6523--6541, 2020. [nlp]
- Embracing Change: Continual Learning in Deep Neural Networks
- Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges - Rodr\ǵuez. *Information Fusion*, 52--68, 2020. [framework]
- A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
- A Review of Off-Line Mode Dataset Shifts - -27, 2020.
- Continual Learning with Neural Networks: A Review - -365, 2019.
- Continual Lifelong Learning with Neural Networks: A Review - -71, 2019. [framework]
- Lifelong Machine Learning, Second Edition
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