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#

domain-incremental-learning

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PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

  • UpdatedNov 5, 2025
  • Jupyter Notebook

RanPAC: Random Projections and Pre-trained Models for Continual Learning - Official code repository for NeurIPS 2023 Published Paper

  • UpdatedFeb 15, 2025
  • Python

[NeurIPS 2023] A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

  • UpdatedJan 26, 2025
  • Python

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning (CVPR 2025)

  • UpdatedJan 28, 2026
  • Python

[ICPR 2024] Exemplar-free continual deepfake detector that leverages CLIP and domain-specific multi-modal prompts

  • UpdatedAug 1, 2024
  • Python

Dual Cognitive Architecture: Incorporating Biases and Multi-Memory Systems for Lifelong Learning

  • UpdatedOct 17, 2023
  • Python

🏷️ multi-label cardinality-incremental experiments of our CVWW 2026 submission.

  • UpdatedJan 21, 2026
  • Jupyter Notebook

Implementation of Dark Experience Replay with Reservoir Sampling from scratch, benchmarked on CIL, TIL and DIL.

  • UpdatedMar 9, 2025
  • Jupyter Notebook

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