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Poster
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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 |
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Poster
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Tue 1:00 |
Calibration tests beyond classification David Widmann · Fredrik Lindsten · Dave Zachariah |
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Poster
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Thu 1:00 |
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning Namyeong Kwon · Hwidong Na · Gabriel Huang · Simon Lacoste-Julien |
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Poster
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Wed 17:00 |
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission Adam Fisch · Tal Schuster · Tommi Jaakkola · Regina Barzilay |
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Poster
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Thu 9:00 |
Uncertainty in Gradient Boosting via Ensembles Andrey Malinin · Liudmila Prokhorenkova · Aleksei Ustimenko |
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Poster
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Mon 9:00 |
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng · Qi Feng · Georgios Karagiannis · Guang Lin · Faming Liang |
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Poster
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Tue 1:00 |
Activation-level uncertainty in deep neural networks Pablo Morales-Alvarez · Daniel Hernández-Lobato · Rafael Molina · José Miguel Hernández Lobato |
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Spotlight
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Mon 13:20 |
Uncertainty Sets for Image Classifiers using Conformal Prediction Anastasios Angelopoulos · Stephen Bates · Michael Jordan · Jitendra Malik |
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Poster
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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 |
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Workshop
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Fri 7:10 |
Poster Spotlight "Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure" Zhijie Deng |
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Poster
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Tue 9:00 |
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán · Umang Bhatt · Tameem Adel · Adrian Weller · José Miguel Hernández Lobato |
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Poster
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Thu 9:00 |
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake Snell · Richard Zemel |