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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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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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Thu 9:00 |
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake Snell · Richard Zemel |
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Poster
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Mon 1:00 |
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs Cheng Wang · Carolin Lawrence · Mathias Niepert |
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Poster
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Tue 9:00 |
Uncertainty-aware Active Learning for Optimal Bayesian Classifier Guang Zhao · Edward Dougherty · Byung-Jun Yoon · Francis Alexander · Xiaoning Qian |
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Workshop
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$\delta$-CLUE: Diverse Sets of Explanations for Uncertainty Estimates Daniel Ley · Umang Bhatt · Adrian Weller |
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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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Tue 9:00 |
Uncertainty Estimation in Autoregressive Structured Prediction Andrey Malinin · Mark Gales |
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Poster
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Thu 9:00 |
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning Kanil Patel · William H Beluch · Bin Yang · Michael Pfeiffer · Dan Zhang |
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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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Wed 9:00 |
Probabilistic Numeric Convolutional Neural Networks Marc Finzi · Roberto Bondesan · Max Welling |
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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 |