Results 11 to 20 of about 24,131 (257)
Logarithmic Continual Learning
IEEE Access, 2022 We introduce a neural network architecture that logarithmically reduces the number of self-rehearsal steps in the generative rehearsal of continually learned models.
Wojciech Masarczyk +4 more
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Learning to Prompt for Continual Learning
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challenge. Typical methods rely on a rehearsal buffer or known task identity at test time to retrieve learned knowledge and address forgetting, while this work presents a new ...
Zifeng Wang 0002 +9 more
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Applied Sciences, 2023 This paper proposes a supervised classification algorithm capable of continual learning by utilizing an Adaptive Resonance Theory (ART)-based growing self-organizing clustering algorithm.
Naoki Masuyama +3 more
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Learning continuous models for continuous physics
Communications Physics, 2023 AbstractDynamical systems that evolve continuously over time are ubiquitous throughout science and engineering. Machine learning (ML) provides data-driven approaches to model and predict the dynamics of such systems. A core issue with this approach is that ML models are typically trained on discrete data, using ML methodologies that are not aware of ...
Aditi S. Krishnapriyan +3 more
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Bilevel Continual Learning [PDF]
2021 International Joint Conference on Neural Networks (IJCNN), 2021 Continual learning (CL) studies the problem of learning a sequence of tasks, one at a time, such that the learning of each new task does not lead to the deterioration in performance on the previously seen ones while exploiting previously learned features.
Ammar Shaker +3 more
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CLRS: Continual Learning Benchmark for Remote Sensing Image Scene Classification
Sensors, 2020 Remote sensing image scene classification has a high application value in the agricultural, military, as well as other fields. A large amount of remote sensing data is obtained every day. After learning the new batch data, scene classification algorithms
Haifeng Li +6 more
doaj +1 more source
Continual Barlow Twins: Continual Self-Supervised Learning for Remote Sensing Semantic Segmentation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 In the field of earth observation (EO), continual learning (CL) algorithms have been proposed to deal with large datasets by decomposing them into several subsets and processing them incrementally.
Valerio Marsocci, Simone Scardapane
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Bookworm continual learning: beyond zero-shot learning and continual learning
CoRR, 2020 Accepted by TASK-CV workshop at ECCV ...
Kai Wang 0060 +3 more
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Continual Learning in Practice [PDF]
CoRR, 2019 Presented at the NeurIPS 2018 workshop on Continual Learning https://sites.google.com/view/continual2018 ...
Tom Diethe +4 more
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Extensible Steganalysis via Continual Learning
Fractal and Fractional, 2022 To realize secure communication, steganography is usually implemented by embedding secret information into an image selected from a natural image dataset, in which the fractal images have occupied a considerable proportion.
Zhili Zhou +3 more
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