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Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.

, , , , , , и . NeurIPS, стр. 3438-3450. (2021)

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Zhang Zhang

Meng Zhang

Methods and implementations of road-network matching. TU München, (2009)

Xianghui Zhang

Le Zhang

Gang Zhang

 

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Rare Event Probability Learning by Normalizing Flows., , , и . CoRR, (2023)PhyloGFN: Phylogenetic inference with generative flow networks., , , , , , , и . ICLR, OpenReview.net, (2024)Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization., , , , , и . CoRR, (2021)Unifying Likelihood-free Inference with Black-box Optimization and Beyond., , , и . ICLR, OpenReview.net, (2022)Out-of-Distribution Generalization via Risk Extrapolation (REx)., , , , , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 5815-5826. PMLR, (2021)PhyloGFN: Phylogenetic inference with generative flow networks., , , , , , , и . CoRR, (2023)Learning to Scale Logits for Temperature-Conditional GFlowNets., , , , , , , и . CoRR, (2023)Unifying Generative Models with GFlowNets., , , и . CoRR, (2022)GFlowOut: Dropout with Generative Flow Networks., , , , , , , , , и 3 other автор(ы). ICML, том 202 из Proceedings of Machine Learning Research, стр. 21715-21729. PMLR, (2023)Informative Dropout for Robust Representation Learning: A Shape-bias Perspective., , , , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 8828-8839. PMLR, (2020)