Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

5 papers of 11,817Sort Recent · Most cited
  1. 2021
    Combining Accuracy and Plasticity in Convolutional Neural Networks Based on Resistive Memory Arrays for Autonomous LearningS. Bianchi, Irene Muñoz-Martín, Erika Covi … Daniele IelminiIEEE Journal on Exploratory Solid-State Computational Dev… · Politecnico di Milano · NaMLab (Germany) · +4
  2. 2021
    A Brain-Inspired Homeostatic Neuron Based on Phase-Change Memories for Efficient Neuromorphic ComputingIrene Muñoz-Martín, S. Bianchi, Shahin Hashemkhani … Daniele IelminiFrontiers · Politecnico di Milano
  3. 2020
    A SiOx, RRAM-based hardware with spike frequency adaptation for power-saving continual learning in convolutional neural networksIrene Muñoz-Martín, S. Bianchi, Erika Covi … Daniele IelminiIEEE Symposium on VLSI Technology · Politecnico di Milano · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · +2
  4. 2020
    Bio-Inspired Techniques in a Fully Digital Approach for Lifelong LearningS. Bianchi, Irene Muñoz-Martín, Daniele IelminiFrontiers · Politecnico di Milano
  5. 2019
    Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapsesS. Bianchi, Irene Muñoz-Martín, Giacomo Pedretti … Daniele IelminiSymposium on VLSI Technology · Politecnico di Milano · IBM Research - Almaden
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. 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.