Incremental Learning
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Incremental learning aims to develop artificially intelligent systems that can continuously learn to address new tasks from new data while preserving knowledge learned from previously learned tasks.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Mattdl/ContinualPrototypeEvolution
공식 코드Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams
https://github.com/MostafaRahgouy/AA-CIL
공식 코드Towards Effective Authorship Attribution: Integrating Class-Incremental Learning
https://github.com/MrPio/KAN-Continual_Learning_tests
공식 코드A preliminary study on continual learning in computer vision using Kolmogorov-Arnold Networks
https://github.com/Natlem/M-HTCN
공식 코드Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer
https://github.com/NeurAI-Lab/AGILE
공식 코드Mitigating Interference in the Knowledge Continuum through Attention-Guided Incremental Learning
https://github.com/NeuralCollapseApplications/FSCIL
공식 코드Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning
https://github.com/Programmergg/NTK-FSCIL
공식 코드https://github.com/QFerdi/FECIL
공식 코드Feature Expansion and enhanced Compression for Class Incremental Learning
https://github.com/ROBOTICSENGINEER/Open_World_Learning_Without_Labels
공식 코드A Review of Open-World Learning and Steps Toward Open-World Learning Without Labels
https://github.com/Rhyssiyan/DER-ClassIL.pytorch
공식 코드DER: Dynamically Expandable Representation for Class Incremental Learning
https://github.com/RingBDStack/KPGNN
공식 코드Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs
https://github.com/RobinLu1209/Geometer
공식 코드Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
https://github.com/SunWenJu123/DCPOC
공식 코드Exemplar-free Class Incremental Learning via Discriminative and Comparable One-class Classifiers
https://github.com/TOM-tym/Learn-to-Imagine
공식 코드Learning to Imagine: Diversify Memory for Incremental Learning using Unlabeled Data
https://github.com/TPCD/LifelongReID
공식 코드Lifelong Person Re-Identification via Adaptive Knowledge Accumulation
https://github.com/ToyotaCRDL/OneShotDIL
공식 코드https://github.com/Tsebeb/cvww_cir_horde
공식 코드Incremental Learning with Repetition via Pseudo-Feature Projection
https://github.com/UTS-AAi/comparative-gfmm
공식 코드A comparative study of general fuzzy min-max neural networks for pattern classification problems
https://github.com/Vastlab/SSFiOWL
공식 코드https://github.com/Vision-sejin/FDCNet
공식 코드https://github.com/YanFangCS/IPSeg
공식 코드IPSeg: Image Posterior Mitigates Semantic Drift in Class-Incremental Segmentation
https://github.com/Yanyi-Zhang/CompILer
공식 코드Not Just Object, But State: Compositional Incremental Learning without Forgetting
https://github.com/YukunLi99/CoLeCLIP
공식 코드CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning
https://github.com/ZHUANGHP/Analytic-continual-learning
공식 코드ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection
https://github.com/abdohelmy/D-3Former
공식 코드D3Former: Debiased Dual Distilled Transformer for Incremental Learning
https://github.com/adekhovich/continual_prune_and_select
공식 코드Continual Prune-and-Select: Class-incremental learning with specialized subnetworks
https://github.com/adityashahane10/gotham--graph-based-class-incremental-learning-framework-under-weak-supervision
공식 코드GOTHAM: Graph Class Incremental Learning Framework under Weak Supervision
https://github.com/ahangchen/TFusion
공식 코드https://github.com/ahmadisahar/accv_fcil3d
공식 코드Foundation Model-Powered 3D Few-Shot Class Incremental Learning via Training-free Adaptor
https://github.com/aignlai/gddsg
공식 코드Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping
https://github.com/aimagelab/casper
공식 코드https://github.com/aimagelab/mammoth
공식 코드A Second-Order Perspective on Model Compositionality and Incremental Learning
https://github.com/algohunt/streamrf
공식 코드https://github.com/aliayub7/CBCL
공식 코드Cognitively-Inspired Model for Incremental Learning Using a Few Examples
https://github.com/aliayub7/cbcl-pr
공식 코드CBCL-PR: A Cognitively Inspired Model for Class-Incremental Learning in Robotics
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.