Incremental Learning
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Benchmarks
Most implemented
Overcoming catastrophic forgetting in neural networks
Learning without Forgetting
iCaRL: Incremental Classifier and Representation Learning
Three scenarios for continual learning
Gradient Episodic Memory for Continual Learning
End-to-End Incremental Learning
Papers
Hyperbolic Geometry for Open-World Object Detection in Remote Sensing Imagery
Open-world object detection (OWOD) extends closed-set detection by requiring models to identify unknown objects and incrementally learn them once annotations become available. In remote sensing imagery, object categories…
Incremental LearningObject DetectionMetric LearningIn Two Minds about Lifelong Learning: Exploring Hemispheric Redundancy and Specialisation in Neural Models
Persistent intelligent systems require the ability to learn continually, but current machine learning approaches face significant challenges in this area compared to biological learning systems. Machine learning algorith…
Incremental LearningContinual LearningSTAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Models
Deep learning models applied to medical image analysis suffer from severe catastrophic forgetting when continually adapting to new clinical tasks in dynamic environments. Mainstream incremental learning methods typically…
Incremental LearningRelative Parameter Importance in Task-Agnostic Replay-Free Continual Learning
Achieving continual learning (CL) with deep neural networks requires balancing stability and plasticity while enabling knowledge transfer. In this work, we focus on offline learning algorithms under the constraints: (I) …
Incremental LearningText ClassificationContinual LearningText GenerationCompactly supported radial basis functions as probability density functions
Compactly Supported Radial Basis Functions (CS-RBFs) are a fundamental tool in multivariate approximation theory. However, their use in statistics and probability modeling remains underexplored, having been used mainly t…
Incremental LearningGaussian ProcessesDensity EstimationOnline Variance Reduction for Domain Adaptation on Streaming Data
This paper studies the problem of stochastic variance reduction (SVR) for the maximum mean discrepancy (MMD) and correlation alignment (CORAL) loss functions. Although various offline SVR algorithms for these losses have…
Incremental LearningDomain Adaptation