Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

10 papers of 8,653Sort Recent · Most cited
  1. 2026
    Dynamic GNNs for Continual Learning on CircuitsRupesh Raj Karn, Johann Knechtel, Ozgur SinanogluIEEE International Symposium on Circuits and Systems (ISCAS) · New York University
  2. 2025
    Multi-Attribute Continual Learning for Blind Image Quality AssessmentYunhao Luo, Jinming Liu, Wei Zhou, Xin JinIEEE International Symposium on Circuits and Systems (ISCAS) · University of Electronic Science and Technology of China · Ningbo Institute of Industrial Technology · +1
  3. 2025
    ZSCIL: Zero-Shot Class Incremental Learning Method for Signal RecognitionWenjie Sun, Rujun Song, Sidi Liang … Bo YanIEEE International Symposium on Circuits and Systems (ISCAS) · University of Electronic Science and Technology of China · Shanghai Jiao Tong University
  4. 2025
    A Quantitative Analysis of Catastrophic Forgetting in Quantized Spiking Neural NetworksAssel Kembay, Karina Aguilar, Jason K. EshraghianIEEE International Symposium on Circuits and Systems (ISCAS) · University of California, Santa Cruz
  5. 2024
    Memory-Based Contrastive Learning with Optimized Sampling for Incremental Few-Shot Semantic SegmentationYuxuan Zhang, Miaojing Shi, Taiyi Su, Hanli WangIEEE International Symposium on Circuits and Systems (ISCAS) · Tongji University
  6. 2024
    On Class-Incremental Learning for Fully Binarized Convolutional Neural NetworksYanis Basso-Bert, William Guicquéro, Anca Molnos … Antoine DupretIEEE International Symposium on Circuits and Systems (ISCAS) · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Laboratoire d'Électronique des Technologies de l'Information · +2
  7. 2022
    SCOLAR: A Spiking Digital Accelerator with Dual Fixed Point for Continual LearningVedant Karia, Fatima Tuz Zohora, Nicholas Soures, Dhireesha KudithipudiIEEE International Symposium on Circuits and Systems (ISCAS) · The University of Texas at San Antonio
  8. 2022
    Edge Computation-in-Memory for In-situ Class-incremental Learning with Knowledge DistillationShinsei Yoshikiyo, Naoko Misawa, Chihiro Matsui, Ken TakeuchiIEEE International Symposium on Circuits and Systems (ISCAS) · Tokyo University of Information Sciences · The University of Tokyo
  9. 2021
    MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual LearningFatima Tuz Zohora, Vedant Karia, Anurag Daram … Dhireesha KudithipudiIEEE International Symposium on Circuits and Systems (ISCAS) · The University of Texas at San Antonio
  10. 2019
    Incremental Learning Meets Reduced Precision NetworksYuhuang Hu, Tobi Delbrück, Shih‐Chii LiuIEEE International Symposium on Circuits and Systems (ISCAS) · SIB Swiss Institute of Bioinformatics · University of Zurich · +1
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.