| Accurate Layerwise Interpretable Competence Estimation | Vickram Rajendran · William LeVine |
| Accurate Uncertainty Estimation and Decomposition in Ensemble Learning | Jeremiah Liu · John Paisley · Marianthi-Anna Kioumourtzoglou · Brent Coull |
| Addressing Failure Detection by Learning Model Confidence | Charles Corbière · Nicolas THOME · Avner Bar-Hen · Matthieu Cord · Patrick Pérez |
| Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration | Meelis Kull · Miquel Perello Nieto · Markus Kängsepp · Telmo Silva Filho · Hao Song · Peter Flach |
| Calibration tests in multi-class classification: A unifying framework | David Widmann · Fredrik Lindsten · Dave Zachariah |
| Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift | Jasper Snoek · Yaniv Ovadia · Emily Fertig · Balaji Lakshminarayanan · Sebastian Nowozin · D. Sculley · Joshua Dillon · Jie Ren · Zachary Nado |
| Computing Full Conformal Prediction Set with Approximate Homotopy | Eugene Ndiaye · Ichiro Takeuchi |
| Conformalized Quantile Regression | Yaniv Romano · Evan Patterson · Emmanuel Candes |
| Deep Gamblers: Learning to Abstain with Portfolio Theory | Ziyin Liu · Zhikang Wang · Paul Pu Liang · Russ Salakhutdinov · Louis-Philippe Morency · Masahito Ueda |
| Likelihood Ratios for Out-of-Distribution Detection | Jie Ren · Peter J. Liu · Emily Fertig · Jasper Snoek · Ryan Poplin · Mark Depristo · Joshua Dillon · Balaji Lakshminarayanan |
| Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections | Raanan Yehezkel Rohekar · Yaniv Gurwicz · Shami Nisimov · Gal Novik |
| Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians | Axel Brando · Jose A Rodriguez · Jordi Vitria · Alberto Rubio Muñoz |
| On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks | Sunil Thulasidasan · Gopinath Chennupati · Jeff Bilmes · Tanmoy Bhattacharya · Sarah Michalak |
| Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees | Muhammad Osama · Dave Zachariah · Peter Stoica |
| Reliable training and estimation of variance networks | Nicki Skafte · Martin Jørgensen · Søren Hauberg |
| Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness | Andrey Malinin · Mark Gales |
| Single-Model Uncertainties for Deep Learning | Natasa Tagasovska · David Lopez-Paz |
| The Functional Neural Process | Christos Louizos · Xiahan Shi · Klamer Schutte · Max Welling |
| Uncertainty on Asynchronous Time Event Prediction | Marin Biloš · Bertrand Charpentier · Stephan Günnemann |
| Verified Uncertainty Calibration | Ananya Kumar · Percy Liang · Tengyu Ma |