Awesome Continual Learning

This repository contains a curated list of continual learning papers and BibTeX entries (mostly until 2022).

Survey
Replay-based
- Memory replay
- Generative replay
Regularization-based
Architecture-based
- Expansion
- Mask
- Decompose
Application

Survey

(Book 18) Lifelong Machine Learning
(PhD dissertation 19) Continual Learning with Deep Architectures
(PhD dissertation 19) Continual Learning in Neural Networks
(Trends in Cognitive Science 20) Embracing Change: Continual Learning in Deep Neural Networks
(TPAMI 21) A Continual Learning Survey: Defying Forgetting in Classification Tasks
(JAIR 22) Towards Continual Reinforcement Learning: A Review and Perspectives
(Neurocomputing 22) Online Continual Learning in Image Classification: An Empirical Survey
(arXiv 22) An Introduction to Lifelong Supervised Learning
(Trends in Neurosciences 23) Continual Task Learning in Natural and Artificial Agents
(Neural Networks 23) A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
(arXiv 23) Deep Class-Incremental Learning: A Survey
(arXiv 23) A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
(TPAMI 24) A Comprehensive Survey of Continual Learning: Theory, Method and Application
(IJCAI 24) Continual Learning with Pre-Trained Models: A Survey

Replay-based

Memory replay

(CVPR 17) iCaRL: Incremental Classifier and Representation Learning
(NeurIPS 17) Gradient Episodic Memory for Continual Learning
(ECCV 18) End-to-End Incremental Learning
(ICLR 19) Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
(ICLR 19) Efficient Lifelong Learning with A-GEM
(CVPR 19) Large Scale Incremental Learning
(CVPR 19) Learning a Unified Classifier Incrementally via Rebalancing
(NeurIPS 19) Experience Replay for Continual Learning
(NeurIPS 19) Gradient based Sample Selection for Online Continual Learning
(NeurIPS 19) Online Continual Learning with Maximal Interfered Retrieval
(ICMLW 19) On Tiny Episodic Memories in Continual Learning
(ECCV 20) GDumb: A Simple Approach that Questions Our Progress in Continual Learning
(NeurIPS 20) Coresets via Bilevel Optimization for Continual Learning and Streaming
(NeurIPS 20) Dark Experience for General Continual Learning: A Strong, Simple Baseline
(ICPR 20) Rethinking Experience Replay: A Bag of Tricks for Continual Learning
(AAAI 21) Using Hindsight to Anchor Past Knowledge in Continual Learning
(ICLR 21) Dataset Condensation with Gradient Matching
(CVPR 21) Rainbow Memory: Continual Learning with a Memory of Diverse Samples
(ICML 21) Grad-Match: Gradient Matching Based Data Subset Selection for Efficient Deep Model Training
(ICCV 21) Rehearsal Revealed: The Limits and Merits of Revisiting Samples in Continual Learning
(NeurIPS 21) Gradient-based Editing of Memory Examples for Online Task-free Continual Learning
(NeurIPS 21) RMM: Reinforced Memory Management for Class-Incremental Learning
(NeurIPSW 21) Gradient-Matching Coresets for Continual Learning
(ICLR 22) Online Coreset Selection for Rehearsal-based Continual Learning
(ICLR 22) New Insights on Reducing Abrupt Representation Change in Online Continual Learning
(ICLR 22) Memory Replay with Data Compression for Continual Learning
(CVPR 22) GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning
(ICML 22) Improving Task-free Continual Learning by Distributionally Robust Memory Evolution
(ICML 22) Online Continual Learning through Mutual Information Maximization
(NeurIPS 22) Exploring Example Influence in Continual Learning
(NeurIPS 22) Retrospective Adversarial Replay for Continual Learning
(NeurIPS 22) Repeated Augmented Rehearsal: A Simple but Strong Baseline for Online Continual Learning
(TPAMI 22) Class-Incremental Continual Learning into the eXtended DER-verse
(ICLR 23) Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning
(CVPR 23) Computationally Budgeted Continual Learning: What Does Matter?
(CVPR 23) Class-Incremental Exemplar Compression for Class-Incremental Learning
(CVPR 23) PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning
(CVPR 23) Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning
(CVPR 23) Regularizing Second-Order Influences for Continual Learning
(ICML 23) BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning
(ICML 23) DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
(IJCV 23) Trust-Region Adaptive Frequency for Online Continual Learning

Generative replay

(NeurIPS 17) Continual Learning with Deep Generative Replay
(NeurIPS 18) Memory Replay GANs: Learning to Generate New Categories without Forgetting
(NeurIPS 20) GAN Memory with No Forgetting
(Nature Communications 20) Brain-Inspired Replay for Continual Learning with Artificial Neural Networks
(Neurocomputing 20) Lifelong Generative Modeling
(ICCV 21) Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning
(CVPR 22) Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data
(ICLR 23) Incremental Learning of Structured Memory via Closed-Loop Transcription
(ICML 23) DDGR: Continual Learning with Deep Diffusion-based Generative Replay

Regularization-based

(ICML 17) Continual Learning through Synaptic Intelligence
(ECCV 18) Memory Aware Synapses: Learning What (Not) to Forget
(ECCV 18) Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
(NeurIPS 20) Understanding the Role of Training Regimes in Continual Learning
(CVPR 23) Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning
(ICLR 24) A Unified and General Framework for Continual Learning

Bayesian-based

(PNAS 17) Overcoming Catastrophic Forgetting in Neural Networks
(NeurIPS 17) Overcoming Catastrophic Forgetting by Incremental Moment Matching
(NeurIPS 18) Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting
(ICLR 18) Variational Continual Learning
(NeurIPS 19) Uncertainty-based Continual Learning with Adaptive Regularization
(ICLR 20) Uncertainty-guided Continual Learning with Bayesian Neural Networks
(ICLR 20) Continual Learning with Adaptive Weights (CLAW)
(NeurIPS 21) Natural Continual Learning: Success Is a Journey, Not (Just) A Destination
(NeurIPS 21) AFEC: Active Forgetting of Negative Transfer in Continual Learning
(AISTATS 22) Provable Continual Learning via Sketched Jacobian Approximations

Subspace-based

(Nature Machine Intelligence 19) Continual Learning of Context-Dependent Processing in Neural Networks
(AISTATS 20) Orthogonal Gradient Descent for Continual Learning
(NeurIPS 20) Continual Learning in Low-rank Orthogonal Subspaces
(ICLR 21) Gradient Projection Memory for Continual Learning
(ICLR 21) Linear Mode Connectivity in Multitask and Continual Learning
(CVPR 21) Training Networks in Null Space of Feature Covariance for Continual Learning
(CVPR 21) Layerwise Optimization by Gradient Decomposition for Continual Learning
(NeurIPS 21) Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
(ICLR 22) TRGP: Trust Region Gradient Projection for Continual Learning
(ICLR 22) Continual Learning with Recursive Gradient Optimization
(ICML 22) Continual Learning with Guarantees via Weight Interval Constraints
(CVPR 22) Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector
(AAAI 23) Continual Learning with Scaled Gradient Projection
(ICLR 23) Building a Subspace of Policies for Scalable Continual Learning
(CVPR 23) Adaptive Plasticity Improvement for Continual Learning
(CVPR 23) Decoupling Learning and Remembering: a Bilevel Memory Framework with Knowledge Projection for Task-Incremental Learning
(ICML 23) Optimizing Mode Connectivity for Class Incremental Learning
(ICCV 23) Data Augmented Flatness-aware Gradient Projection for Continual Learning
(ICLR 24) Prompt Gradient Projection for Continual Learning

Distillation-based

(TPAMI 17) Learning without Forgetting
(CVPR 19) Learning without Memorizing
(CVPR 20) Few-Shot Class-Incremental Learning
(ECCV 20) Topology-Preserving Class-Incremental Learning
(ICCV 21) Co^2^L: Contrastive Continual Learning
(TIP 22) CKDF: Cascaded Knowledge Distillation Framework for Robust Incremental Learning
(TPAMI 23) Variational Data-Free Knowledge Distillation for Continual Learning
(ICML 23) Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
(ICCV 23) Dynamic Residual Classifier for Class Incremental Learning
(ICCV 23) Prototype Reminiscence and Augmented Asymmetric Knowledge Aggregation for Non-Exemplar Class-Incremental Learning

Architecture-based

(ICLR 20) Continual Learning with Hypernetworks
(NeurIPS 21) DualNet: Continual Learning, Fast and Slow
(ICLR 22) Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System
(ICLR 22) Model Zoo: A Growing Brain That Learns Continually
(ECCV 22) CoSCL: Cooperation of Small Continual Learners is Stronger Than a Big One
(CVPR 23) Bilateral Memory Consolidation for Continual Learning
(ICCV 23) Growing a Brain with Sparsity-Inducing Generation for Continual Learning
(ICLR 24) Divide and Not Forget: Ensemble of Selectively Trained Experts in Continual Learning
(AAAI 24) Evolving Parameterized Prompt Memory for Continual Learning

Expansion

(ICLR 16) Net2Net: Accelerating Learning via Knowledge Transfer
(arXiv 16) Progressive Neural Networks
(CVPR 17) Expert Gate: Lifelong Learning with a Network of Experts
(ICML 17) AdaNet: Adaptive Structural Learning of Artificial Neural Networks
(ICLR 18) Lifelong Learning with Dynamically Expandable Networks
(ICML 19) Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
(ICLR 20) A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning
(ECCV 20) Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks
(NeurIPS 20) Calibrating CNNs for Lifelong Learning
(CVPR 21) DER: Dynamically Expandable Representation for Class Incremental Learning
(CVPR 21) Adaptive Aggregation Networks for Class-Incremental Learning
(NeurIPS 21) BNS: Building Network Structures Dynamically for Continual Learning
(CVPR 22) DyTox: Transformers for Continual Learning with Dynamic Token Expansion
(CVPR 22) Learning to Prompt for Continual Learning
(ECCV 22) DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning
(ECCV 22) FOSTER: Feature Boosting and Compression for Class-Incremental Learning
(NeurIPS 22) S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning
(TPAMI 22) Adaptive Progressive Continual Learning
(ICLR 23) Progressive Prompts: Continual Learning for Language Models
(ICLR 23) A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
(CVPR 23) Task Difficulty Aware Parameter Allocation & Regularization for Lifelong Learning
(CVPR 23) Dense Network Expansion for Class Incremental Learning
(CVPR 23) DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning
(CVPR 23) CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning
(ICML 23) Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
(ICML 23) Lifelong Language Pretraining with Distribution-Specialized Experts
(ICCV 23) A Unified Continual Learning Framework with General Parameter-Efficient Tuning
(ICCV 23) CLR: Channel-wise Lightweight Reprogramming for Continual Learning
(ICCV 23) Exemplar-Free Continual Transformer with Convolutions
(ICCV 23) Self-Evolved Dynamic Expansion Model for Task-Free Continual Learning
(ICCV 23) Tangent Model Composition for Ensembling and Continual Fine-tuning
(ICCV 23) Generating Instance-level Prompts for Rehearsal-free Continual Learning
(ICCV 23) Self-Organizing Pathway Expansion for Non-Exemplar Class-Incremental Learning
(NeurIPS 23) Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality

Mask

(CVPR 18) PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning
(ICML 18) Overcoming Catastrophic Forgetting with Hard Attention to the Task
(NeurIPS 19) Random Path Selection for Incremental Learning
(NeurIPSW 19) Continual Learning via Neural Pruning
(NeurIPS 20) Supermasks in Superposition
(ICLR 21) Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning
(CVPR 21) Continual Learning via Bit-Level Information Preserving
(CVPR 22) Meta-Attention for ViT-backed Continual Learning
(ICML 22) Forget-free Continual Learning with Winning Subnetworks
(ICML 22) NISPA: Neuro-Inspired Stability-Plasticity Adaptation for Continual Learning in Sparse Networks
(ICML 23) Discrete Key-Value Bottleneck
(ICML 23) Parameter-Level Soft-Masking for Continual Learning
(ICLR 24) Scalable Language Model With Generalized Continual Learning
(AAAI 24) MIND: Multi-Task Incremental Network Distillation

Decompose

(ICLR 20) Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
(ICLR 20) BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
(CVPR 21) Efficient Feature Transformations for Discriminative and Generative Continual Learning
(NeurIPS 21) Mitigating Forgetting in Online Continual Learning with Neuron Calibration
(NeurIPS 21) Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning
(ICLR 22) TRGP: Trust Region Gradient Projection for Continual Learning

Application

Object detection

(ICCV 17) Incremental Learning of Object Detectors without Catastrophic Forgetting
(WACV 20) Class-incremental Learning via Deep Model Consolidation
(CVPR 20) Incremental Few-Shot Object Detection
(CVPR 21) Towards Open World Object Detection
(ICCV 21) Wanderlust: Online Continual Object Detection in the Real World
(NeurIPS 21) Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
(TPAMI 21) Incremental Object Detection via Meta-Learning
(CVPR 22) Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation
(CVPR 22) Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
(CVPR 22) OW-DETR: Open-world Detection Transformer
(ECCV 22) UC-OWOD: Unknown-Classified Open World Object Detection
(CVPR 23) Continual Detection Transformer for Incremental Object Detection
(CVPR 23) CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection
(CVPR 23) PROB: Probabilistic Objectness for Open World Object Detection
(CVPR 23) Annealing-based Label-Transfer Learning for Open World Object Detection
(ICCV 23) Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection
(ICCV 23) Label-Efficient Online Continual Object Detection in Streaming Video
(ICCV 23) Random Boxes Are Open-world Object Detectors
(CVPR 24) SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
(CVPR 24) Exploring Orthogonality in Open World Object Detection

Semantic segmentation

(ICCVW 19) Incremental Learning Techniques for Semantic Segmentation
(CVPR 20) Modeling the Background for Incremental Learning in Semantic Segmentation
(AAAI 21) A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation
(AAAI 21) Unsupervised Model Adaptation for Continual Semantic Segmentation
(CVPR 21) Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
(CVPR 21) PLOP: Learning without Forgetting for Continual Semantic Segmentation
(CVPR 21) Incremental Few-Shot Instance Segmentation
(ICCV 21) RECALL: Replay-based Continual Learning in Semantic Segmentation
(NeurIPS 21) SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
(WACV 22) Multi-Domain Incremental Learning for Semantic Segmentation
(CVPR 22) Representation Compensation Networks for Continual Semantic Segmentation
(CVPR 22) Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation
(CVPR 22) Incremental Learning in Semantic Segmentation from Image Labels
(CVPR 22) Learning Multiple Dense Prediction Tasks from Partially Annotated Data
(ECCV 22) RBC: Rectifying the Biased Context in Continual Semantic Segmentation
(ECCV 22) Continual Semantic Segmentation via Structure Preserving and Projected Feature Alignment
(NeurIPS 22) Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation
(NeurIPS 22) ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation
(NeurIPS 22) Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
(TPAMI 22) Modeling the Background for Incremental and Weakly-Supervised Semantic Segmentation
(TPAMI 22) Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
(TNNLS 22) Self-Training for Class-Incremental Semantic Segmentation
(CVPR 23) Foundation Model Drives Weakly Incremental Learning for Semantic Segmentation
(CVPR 23) CoMFormer: Continual Learning in Semantic and Panoptic Segmentation
(CVPR 23) Continual Semantic Segmentation with Automatic Memory Sample Selection
(CVPR 23) Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather Conditions
(CVPR 23) Unsupervised Continual Semantic Adaptation through Neural Rendering
(CVPR 23) Federated Incremental Semantic Segmentation
(CVPR 23) Incrementer: Transformer for Class-Incremental Semantic Segmentation with Knowledge Distillation Focusing on Old Class
(CVPR 23) Endpoints Weight Fusion for Class Incremental Semantic Segmentation
(ICCV 23) Label-Guided Knowledge Distillation for Continual Semantic Segmentation on 2D Images and 3D Point Clouds
(ICCV 23) Preparing the Future for Continual Semantic Segmentation
(ICCV 23) Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision
(NeurIPS 23) Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments
(CVPR 24) Continual Segmentation with Disentangled Objectness Learning and Class Recognition

Image generation

(NeurIPS 18) Memory Replay GANs: Learning to Generate New Categories without Forgetting
(ICCV 19) Lifelong GAN: Continual Learning for Conditional Image Generation
(ECCV 20) Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
(CVPR 21) Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation
(CVPR 21) Efficient Feature Transformations for Discriminative and Generative Continual Learning
(ICCV 23) LFS-GAN: Lifelong Few-Shot Image Generation
(NeurIPS 23) Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models

Person re-identification

(AVSS 19) Continuous Learning without Forgetting for Person Re-Identification
(AAAI 21) Generalising without Forgetting for Lifelong Person Re-Identification
(WACV 21) Continual Representation Learning for Biometric Identification
(CVPR 21) Lifelong Person Re-Identification via Adaptive Knowledge Accumulation
(AAAI 22) Lifelong Person Re-identification by Pseudo Task Knowledge Preservation
(CVPR 22) Lifelong Unsupervised Domain Adaptive Person Re-Identification with Coordinated Anti-forgetting and Adaptation
(ACM MM 22) Meta Reconciliation Normalization for Lifelong Person Re-Identification
(ACM MM 22) Patch-based Knowledge Distillation for Lifelong Person Re-Identification
(BMVC 22) Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification
(ACM MM 23) Handling Label Uncertainty for Camera Incremental Person Re-Identification
(CVPR 24) Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification
(CVPR 24) Learning Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification

Vision-language learning

(ACL 19) Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering
(EMNLP 20) Visually Grounded Continual Learning of Compositional Phrases
(NeurIPS 20) RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning
(ECCV 22) Generative Negative Text Replay for Continual Vision-Language Pretraining
(NeurIPS 22) BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling
(AAAI 23) Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task
(CVPR 23) ConStruct-VL: Data-Free Continual Structured VL Concepts Learning
(CVPR 23) VQACL: A Novel Visual Question Answering Continual Learning Setting
(ICML 23) Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization
(ICML 23) Continual Vision-Language Representation Learning with Off-Diagonal Information
(ICCV 23) Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
(ICCV 23) CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation
(ICCV 23) Decouple Before Interact: Multi-Modal Prompt Learning for Continual Visual Question Answering
(AAAI 24) Continual Vision-Language Retrieval via Dynamic Knowledge Rectification
(ICLR 24) TiC-CLIP: Continual Training of CLIP Models
(CVPR 24) Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters

Reinforcement learning

(AAAI 18) Selective Experience Replay for Lifelong Learning
(ICLR 18) Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
(ICLR 18) Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
(ICML 18) State Abstractions for Lifelong Reinforcement Learning
(ICML 18) Policy and Value Transfer in Lifelong Reinforcement Learning
(ICML 18) Continual Reinforcement Learning with Complex Synapses
(NeurIPS 18) Lifelong Inverse Reinforcement Learning
(ICLR 19) Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL
(ICLR 19) Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
(ICML 19) Policy Consolidation for Continual Reinforcement Learning
(NeurIPS 19) Experience Replay for Continual Learning
(NeurIPS 20) Deep Reinforcement and InfoMax Learning
(NeurIPS 20) Continual Learning of Control Primitives: Skill Discovery via Reset-Games
(NeurIPS 20) Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
(NeurIPS 20) Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting
(ICLR 21) CoMPS: Continual Meta Policy Search
(ICLR 21) Reset-Free Lifelong Learning with Skill-Space Planning
(Neurocomputing 21) Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting
(AAAI 22) Same State, Different Task: Continual Reinforcement Learning without Interference
(ICLR 22) Modular Lifelong Reinforcement Learning via Neural Composition
(ICLR 22) Generalisation in Lifelong Reinforcement Learning through Logical Composition
(NeurIPS 22) Model-based Lifelong Reinforcement Learning with Bayesian Exploration
(NeurIPS 22) Continual Learning In Environments With Polynomial Mixing Times
(NeurIPS 22) Disentangling Transfer in Continual Reinforcement Learning
(ICLR 23) Building a Subspace of Policies for Scalable Continual Learning
(ICML 23) Continual Task Allocation in Meta-Policy Network via Sparse Prompting
(NeurIPS 23) A Definition of Continual Reinforcement Learning
(NeurIPS 23) Rewiring Neurons in Non-Stationary Environments

Non-stationary MDP

(NeurIPS 19) A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning
(NeurIPS 19) Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning
(AAAI 20) Lifelong Learning with a Changing Action Set
(ICML 20) Optimizing for the Future in Non-Stationary MDPs
(NeurIPS 20) Dynamic Regret of Policy Optimization in Non-stationary Environments
(NeurIPS 20) Towards Safe Policy Improvement for Non-Stationary MDPs
(AAAI 21) Lipschitz Lifelong Reinforcement Learning
(ICML 21) Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
(ICLR 22) Reinforcement Learning in Presence of Discrete Markovian Context Evolution
(NeurIPS 22) Off-Policy Evaluation for Action-Dependent Non-stationary Environments
(NeurIPS 22) Factored Adaptation for Non-Stationary Reinforcement Learning

Others

(SIGGRAPH 19) Unsupervised Incremental Learning for Hand Shape and Pose Estimation
(AAAI 20) Generative Continual Concept Learning
(CVPR 20) Online Depth Learning against Forgetting in Monocular Videos
(ECCV 20) SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
(IROS 20) Latent Replay for Real-Time Continual Learning
(CVPRW 20) Continual Learning for Anomaly Detection in Surveillance Videos
(CVPRW 20) Continual Learning of Object Instances
(ICMLW 20) Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization
(arXiv 20) Learning Causal Models Online
(AAAI 21) Continual Learning for Named Entity Recognition
(CVPR 21) Image De-raining via Continual Learning
(CVPRW 21) Selective Replay Enhances Learning in Online Continual Analogical Reasoning
(ICCV 21) Class-Incremental Learning for Action Recognition in Videos
(ICCV 21) Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data
(ICCV 21) Detection and Continual Learning of Novel Face Presentation Attacks
(ICCV 21) Continual Learning for Image-Based Camera Localization
(ICCV 21) Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations
(BMVC 21) Incremental Learning for Animal Pose Estimation using RBF k-DPP
(WWW 22) Multimodal Continual Graph Learning with Neural Architecture Search
(CVPR 22) Lifelong Graph Learning
(CVPR 22) Continual Test-Time Domain Adaptation
(ICML 22) Efficient Test-Time Model Adaptation without Forgetting
(ECCV 22) Novel Class Discovery without Forgetting
(ECCV 22) incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection
(AISTATS 22) Online Continual Adaptation with Active Self-Training
(ACL 22) Continual Prompt Tuning for Dialog State Tracking
(Findings of ACL 22) Consistent Representation Learning for Continual Relation Extraction
(COLING 22) Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuning
(RA-L 22) Improving Pedestrian Prediction Models with Self-Supervised Continual Learning
(ICLR 23) Towards Open Temporal Graph Neural Networks
(WWW 23) Dynamically Expandable Graph Convolution for Streaming Recommendation
(CVPR 23) Cloud-Device Collaborative Adaptation to Continual Changing Environments in the Real-world
(CVPR 23) PIVOT: Prompting for Video Continual Learning
(CVPR 23) Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation
(ICCV 23) CLNeRF: Continual Learning Meets NeRF
(ICCV 23) Active Neural Mapping
(ICCV 23) GFM: Building Geospatial Foundation Models via Continual Pretraining
(ICCV 23) Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less
(ICCV 23) Towards Realistic Evaluation of Industrial Continual Learning Scenarios with an Emphasis on Energy Consumption and Computational Footprint
(NeurIPS 23) Temporal Continual Learning with Prior Compensation for Human Motion Prediction
(NeurIPS 23) CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation
(ICLR 24) Online Continual Learning for Interactive Instruction Following Agents
(ICLR 24) Two-stage LLM Fine-tuning with Less Specialization and More Generalization
(ICLR 24) CPPO: Continual Learning for Reinforcement Learning With Human Feedback
(ICLR 24) Scalable Language Model with Generalized Continual Learning
(CVPR 24) GOAT-Bench: A Benchmark for Multi-modal Lifelong Navigation

feifeiobama / awesome-continual-learning Goto Github PK

awesome-continual-learning's Introduction

Awesome Continual Learning

Survey

Replay-based

Memory replay

Generative replay

Regularization-based

Bayesian-based

Subspace-based

Distillation-based

Architecture-based

Expansion

Mask

Decompose

Application

Object detection

Semantic segmentation

Image generation

Person re-identification

Vision-language learning

Reinforcement learning

Non-stationary MDP

Others

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