Andrea Cossu

Orcid: 0000-0002-4874-8830

According to our database1, Andrea Cossu authored at least 22 papers between 2020 and 2023.

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Bibliography

2023
Deep Continual Learning (Dagstuhl Seminar 23122).
Dagstuhl Reports, March, 2023

Continual Learning: Applications and the Road Forward.
CoRR, 2023

A Protocol for Continual Explanation of SHAP.
CoRR, 2023

Projected Latent Distillation for Data-Agnostic Consolidation in Distributed Continual Learning.
CoRR, 2023

Avalanche: A PyTorch Library for Deep Continual Learning.
CoRR, 2023

A Comprehensive Empirical Evaluation on Online Continual Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Class-Incremental Learning with Repetition.
Proceedings of the Conference on Lifelong Learning Agents, 2023

2022
Is Class-Incremental Enough for Continual Learning?
Frontiers Artif. Intell., 2022

Catastrophic Forgetting in Deep Graph Networks: A Graph Classification Benchmark.
Frontiers Artif. Intell., 2022

Continual Pre-Training Mitigates Forgetting in Language and Vision.
CoRR, 2022

Sample Condensation in Online Continual Learning.
Proceedings of the International Joint Conference on Neural Networks, 2022

Practical Recommendations for Replay-Based Continual Learning Methods.
Proceedings of the Image Analysis and Processing. ICIAP 2022 Workshops, 2022

Continual Learning for Human State Monitoring.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

Ex-Model: Continual Learning from a Stream of Trained Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Continual learning for recurrent neural networks: An empirical evaluation.
Neural Networks, 2021

Sustainable Artificial Intelligence through Continual Learning.
CoRR, 2021

Avalanche: an End-to-End Library for Continual Learning.
CoRR, 2021

Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification.
CoRR, 2021

Distilled Replay: Overcoming Forgetting Through Synthetic Samples.
Proceedings of the Continual Semi-Supervised Learning - First International Workshop, 2021

Continual Learning with Echo State Networks.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021


2020
Continual Learning with Gated Incremental Memories for sequential data processing.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020


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