Statistical Learning
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection Xinting Liao
Neural Information Processing Systems
FL further makes efforts to adapt real-world scenarios, i.e., adapting
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EigenVI: score-based variational inference with orthogonal function expansions
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We develop EigenVI, an eigenvalue-based approach for black-box variational inference (BBVI).
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Molecule Generation with Fragment Retrieval Augmentation Seul Lee
Neural Information Processing Systems
Work done during an internship at NVIDIA.
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Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
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The CCP method finds the class-wise quantiles of non-conformity scores on calibration data.
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Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
Neural Information Processing Systems
One key challenge in Out-of-Distribution (OOD) detection is the absence of ground-truth OOD samples during training.
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