Understanding anxiety through uncertainty quantification von Hedley, Friederike Elisabeth, Larsen, Emmett, Mohanty, Aprajita, Liu, Jeremiah Zhe, Jin, Jingwen

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Immune Markers and Their Association with Bone Density in Children, Adolescents, and Young Adults with Perinatally Acquired HIV von Jacobson, Denise, Liu, Jeremiah Zhe, Lindsey, Jane C., Shiau, Stephanie, Coull, Brent, Aldrovandi, Grace

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A Cross-Validated Ensemble Approach to Robust Hypothesis Testing of Continuous Nonlinear Interactions: Application to Nutrition-Environment Studies von Liu, Jeremiah Zhe, Deng, Wenying, Lee, Jane, Lin, Pi-i Debby, Valeri, Linda, Christiani, David C., Bellinger, David C., Wright, Robert O., Mazumdar, Maitreyi M., Coull, Brent A.

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Practical Semiparametric Inference With Bayesian Nonparametric Ensembles von Liu, Jeremiah Zhe

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Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon von Liu, Jeremiah Zhe

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Gaussian Process Regression and Classification under Mathematical Constraints with Learning Guarantees von Liu, Jeremiah Zhe

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Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play von Liu, Jeremiah Zhe, Dvijotham, Krishnamurthy Dj, Lee, Jihyeon, Yuan, Quan, Strobel, Martin, Lakshminarayanan, Balaji, Ramachandran, Deepak

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Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes von Liu, Jeremiah Zhe, Coull, Brent

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Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon von Liu, Jeremiah Zhe

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Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees von Deng, Wenying, Coker, Beau, Mukherjee, Rajarshi, Liu, Jeremiah Zhe, Coull, Brent A

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A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models von Allingham, James Urquhart, Ren, Jie, Dusenberry, Michael W, Gu, Xiuye, Cui, Yin, Tran, Dustin, Liu, Jeremiah Zhe, Lakshminarayanan, Balaji

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Gaussian Process Regression and Classification under Mathematical Constraints with Learning Guarantees von Liu, Jeremiah Zhe

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Accurate Uncertainty Estimation and Decomposition in Ensemble Learning von Liu, Jeremiah Zhe, Paisley, John, Kioumourtzoglou, Marianthi-Anna, Coull, Brent

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Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior von Lin, Zi, Liu, Jeremiah Zhe, Yang, Zi, Hua, Nan, Roth, Dan

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CVEK: Robust Estimation and Testing for Nonlinear Effects using Kernel Machine Ensemble von Deng, Wenying, Liu, Jeremiah Zhe, Lake, Erin, Coull, Brent A

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A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness von Liu, Jeremiah Zhe, Padhy, Shreyas, Ren, Jie, Lin, Zi, Wen, Yeming, Jerfel, Ghassen, Nado, Zack, Snoek, Jasper, Tran, Dustin, Lakshminarayanan, Balaji

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Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness von Liu, Jeremiah Zhe, Lin, Zi, Padhy, Shreyas, Tran, Dustin, Bedrax-Weiss, Tania, Lakshminarayanan, Balaji

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Training independent subnetworks for robust prediction von Havasi, Marton, Jenatton, Rodolphe, Fort, Stanislav, Liu, Jeremiah Zhe, Snoek, Jasper, Lakshminarayanan, Balaji, Dai, Andrew M, Tran, Dustin

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Adaptive Ensemble Learning of Spatiotemporal Processes with Calibrated Predictive Uncertainty: A Bayesian Nonparametric Approach von Liu, Jeremiah Zhe, Paisley, John, Kioumourtzoglou, Marianthi-Anna, Coull, Brent A

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Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play von Liu, Jeremiah Zhe, Krishnamurthy Dj Dvijotham, Lee, Jihyeon, Yuan, Quan, Strobel, Martin, Lakshminarayanan, Balaji, Ramachandran, Deepak

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