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We introduce a new problem in unsupervised domain adaptation, termed as Generalized Universal Domain Adaptation (GUDA), which aims to achieve precise prediction of all target labels including unknown categories.
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DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks
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Regularized Offline GFlowNets
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Instrumental Variable-Driven Domain Generalization with Unobserved Confounders
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Visda: A synthetic-to-real benchmark for visual domain adaptation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops . 2021–2026
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Domain-adversarial training of neural networks
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