On Sequential Bayesian Inference for Continual Learning [PDF]
Entropy, 2023 Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks.
Samuel Kessler +4 more
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Is Class-Incremental Enough for Continual Learning? [PDF]
Frontiers in Artificial Intelligence, 2022 The ability of a model to learn continually can be empirically assessed in different continual learning scenarios. Each scenario defines the constraints and the opportunities of the learning environment.
Andrea Cossu +7 more
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Lifelong nnU-Net: a framework for standardized medical continual learning [PDF]
Scientific Reports, 2023 As the enthusiasm surrounding Deep Learning grows, both medical practitioners and regulatory bodies are exploring ways to safely introduce image segmentation in clinical practice.
Camila González +4 more
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Privacy-preserving continual learning methods for medical image classification: a comparative analysis [PDF]
Frontiers in Medicine, 2023 BackgroundThe implementation of deep learning models for medical image classification poses significant challenges, including gradual performance degradation and limited adaptability to new diseases.
Tanvi Verma +14 more
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Continual learning classification method with human-in-the-loop [PDF]
MethodsX, 2023 The classification problem is essential to machine learning, often used in fault detection, condition monitoring, and behavior recognition. In recent years, due to the rapid development of incremental learning, reinforcement learning, transfer learning ...
Jia Liu +3 more
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Cross paradigm fusion of federated and continual learning on multilayer perceptron mixer architecture for incremental thoracic infection diagnosis [PDF]
Scientific ReportsMedical imaging is essential in the study of chest virus infections. Due to data sovereignty issues in healthcare, it is essential to employ federated learning to overcome these obstacles.
Tianshuo Zhou, Boyuan Wang
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Electrochemical ohmic memristors for continual learning [PDF]
Nature CommunicationsDeveloping versatile and reliable memristive devices is crucial for advancing future memory and computing architectures. The years of intensive research have still not reached and demonstrated their full horizon of capabilities, and new concepts are ...
Shaochuan Chen +5 more
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Probabilistic metaplasticity for continual learning with memristors in spiking networks [PDF]
Scientific ReportsEdge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning entails memory
Fatima Tuz Zohora +3 more
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Structuring Continual Learning Through a Hierarchy of Objectives: A Conceptual Framework [PDF]
SAGE Open NursingBackground Continual learning is fundamental for developing critical thinking and problem-solving skills. Although learning activities are well established in education, the connection between objectives, activities, and learning outcomes is often ...
Alette H. Svellingen PhD +2 more
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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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