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Thu 17:00 Combining Ensembles and Data Augmentation Can Harm Your Calibration
Yeming Wen · Ghassen Jerfel · Rafael Müller · Michael W Dusenberry · Jasper Snoek · Balaji Lakshminarayanan · Dustin Tran
Tue 1:00 Calibration tests beyond classification
David Widmann · Fredrik Lindsten · Dave Zachariah
Thu 1:00 Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
Namyeong Kwon · Hwidong Na · Gabriel Huang · Simon Lacoste-Julien
Wed 17:00 Efficient Conformal Prediction via Cascaded Inference with Expanded Admission
Adam Fisch · Tal Schuster · Tommi Jaakkola · Regina Barzilay
Thu 9:00 Uncertainty in Gradient Boosting via Ensembles
Andrey Malinin · Liudmila Prokhorenkova · Aleksei Ustimenko
Mon 9:00 Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng · Qi Feng · Georgios Karagiannis · Guang Lin · Faming Liang
Tue 1:00 Activation-level uncertainty in deep neural networks
Pablo Morales-Alvarez · Daniel Hernández-Lobato · Rafael Molina · José Miguel Hernández Lobato
Mon 13:20 Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Angelopoulos · Stephen Bates · Michael Jordan · Jitendra Malik
Thu 17:00 In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve · Kevin Duarte · Yogesh S Rawat · Mubarak Shah
Fri 7:10 Poster Spotlight "Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure"
Zhijie Deng
Tue 9:00 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán · Umang Bhatt · Tameem Adel · Adrian Weller · José Miguel Hernández Lobato
Thu 9:00 Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes
Jake Snell · Richard Zemel