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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning., , , , , , , , , and 14 other author(s). CoRR, (2021)A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 2260-2268. PMLR, (2019)Foundations of Sequence-to-Sequence Modeling for Time Series., and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 408-417. PMLR, (2019)Population-Based Black-Box Optimization for Biological Sequence Design., , , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 324-334. PMLR, (2020)Learning Determinantal Point Processes by Sampling Inferred Negatives., , and . CoRR, (2018)Pre-training helps Bayesian optimization too., , , , , , , , and . CoRR, (2022)Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling., , , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 3961-3969. PMLR, (2021)Learning Determinantal Point Processes by Corrective Negative Sampling., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2251-2260. PMLR, (2019)Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling., , , , , and . CoRR, (2020)Fixed-point algorithms for determinantal point processes., and . CoRR, (2015)