mlsanityData to 7 Oct 2026

Elastic Weight Consolidation (EWC): Nuts and Bolts

arXiv 2105.04093 ↗First posted 10 May 2021cs.CV cs.LG stat.MLcited by 21

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Abstract (arXiv)

In this report, we present a theoretical support of the continual learning method Elastic Weight Consolidation, introduced in paper titled `Overcoming catastrophic forgetting in neural networks'. Being one of the most cited paper in regularized methods for continual learning, this report disentangles the underlying concept of the proposed objective function. We assume that the reader is aware of the basic terminologies of continual learning.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 6 of its 11 references that are in the map. First posted on arXiv 10 May 2021.

Builds on

6 of 11 references.

References · 6

  1. 2016Overcoming catastrophic forgetting in neural networkscited by 4,718
  2. 2016Learning without Forgettingcited by 2,465
  3. 2017Memory Aware Synapses: Learning what (not) to forgetcited by 1,094
  4. 2019Three scenarios for continual learningcited by 610
  5. 2018Continuous Learning in Single-Incremental-Task Scenarioscited by 109
  6. 2019Localizing Catastrophic Forgetting in Neural Networkscited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 6; 2025: 5; 2026: 6.

21 papers.

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  1. 2023Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampeningcited by 177
  2. 2025On the Computation of the Fisher Information in Continual Learningcited by 12
  3. 2026CORAL: Scalable Multi-Task Robot Learning via LoRA Expertscited by 8
  4. 2026CRL-VLA: Continual Vision-Language-Action Learningcited by 5
  5. 2026PASs-MoE: Mitigating Misaligned Co-drift among Router and Experts via Pathway Activation Subspaces for Continual Learningcited by 4
  6. 2024CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidationcited by 3
  7. 2024CLASSP: a Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity Promotioncited by 2
  8. 2025MLLM-CTBench: A Benchmark for Continual Instruction Tuning with Reasoning Process Diagnosiscited by 2
  9. 2025Provably Safe Model Updatescited by 2
  10. 2026SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operatorscited by 2
  11. 2024Sequential Learning in the Dense Associative Memorycited by 1
  12. 2025SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Modelscited by 1
9 more
  1. 2025A Study on Regularization-Based Continual Learning Methods for Indic ASRcited by 1
  2. 2021The Role of Bio-Inspired Modularity in General Learningcited by 0
  3. 2022GMM-IL: Image Classification using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizescited by 0
  4. 2023The Effect of Masking Strategies on Knowledge Retention by Language Modelscited by 0
  5. 2024Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Networkcited by 0
  6. 2024Low-Rank Filtering and Smoothing for Sequential Deep Learningcited by 0
  7. 2024From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19cited by 0
  8. 2026Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfercited by 0
  9. 2026Attention-based Experience Replay Framework for Continual Learning of Agnostic Time Series Forecasting Modelscited by 0