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Found 3 papers, 1 papers with code
Deep Active Learning with Manifold-preserving Trajectory Sampling
The key question in AL is which unlabeled data should be selected for annotation.
UniAutoML: A Human-Centered Framework for Unified Discriminative and Generative AutoML with Large Language Models
Additionally, these frameworks lack interpretability and user engagement during the training process, primarily due to the absence of human-centered design.
Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design
Our work addresses this challenge by enhancing the detection and management of OOD samples in neural networks.
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