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Contributed Papers

Uncertainty Quantification in Complex Systems IG Contributed

Tue, Aug 4, 2:00 PM - 3:50 PM Room CC-212 Thomas M. Menino Convention & Exhibition Center

David CorlissChair

Uncertainty Quantification in Complex Systems Interest Group

7 Presentations

Extended Fiducial Inference for Statistical Models with Unknown Noise Distributions

2:05 PM - 2:20 PM

Wen-Hung Wang (Purdue Statistics)

Co-authors: Faming Liang (Purdue University)

Adaptive Stochastic Gradient MCMC Fiducial Inference Nonparametric Statistics Uncertainty Quantification Robust Statistics

Last-Layer Adaptive Score Tuning with the Skewed Generalized-t Family

2:20 PM - 2:35 PM

Chun-Hao Yang (National Taiwan University)

Deep Learning Uncertainty Quantification Calibration Bayesian Neural Network

Managing Classification Uncertainty Using Neutral Zones

2:35 PM - 2:50 PM

Classification uncertainty Hypothesis testing Statistical decision theory

Optimality of Sub-network Laplace Approximations: New Results and Methods

2:50 PM - 3:05 PM

Swarnali Raha (University of Florida)

Co-authors: Kshitij Khare (University of Florida), Rohit Patra (Columbia University)

Uncertainty Quantification Posterior Predictive Distributions Linearized Laplace approximation Subset Selection Methods Bayesian Neural Networks Gradient-based thresholding

Probabilistic B-Spline Modeling for Uncertainty Quantification in Ordinary Differential Equations

3:05 PM - 3:20 PM

Carter Hall (North Carolina State University)

Co-authors: Sujit Ghosh (North Carolina State University)

Ordinary Differential Equations Uncertainty Quantification B-Splines Slice sampling Demmler-Reinsch basis Posterior contraction

Uncertainty Quantification of Next Gen Reservoir Computing with Applications to Dynamical Systems

3:20 PM - 3:35 PM

Co-authors: Martin Wells (Department of Statistics and Data Science, Cornell University), Sumanta Basu (Cornell University)

Integro-differential systems Next Generation Reservoir Computing (NGRC)Nonlinear vector autoregression (NVAR)Uncertainty quantification (UQ)Bayesian shrinkage / credible bands Adaptive conformal prediction

Uncertainty-Aware Ordinal Prediction under Noisy Labels for Knee Osteoarthritis Imaging

3:35 PM - 3:50 PM

Jasper Zhongyuan Zhang (University of Toronto)

Co-authors: Xinyi Wang (McMaster University), Ziqian Zhuang, Divya Sharma, Osvaldo Espin-Garcia (University of Western Ontario), Wei Xu (University of Toronto)

Knee osteoarthritis Ordinal classification Medical imaging Uncertainty quantification Label noise Conformal prediction

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