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Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation


Oct 15, 2021
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang


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Sparse MoEs meet Efficient Ensembles


Oct 07, 2021
James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton

* 44 pages, 19 figures, 24 tables 

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Deep Classifiers with Label Noise Modeling and Distance Awareness


Oct 06, 2021
Vincent Fortuin, Mark Collier, Florian Wenzel, James Allingham, Jeremiah Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou


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Soft Calibration Objectives for Neural Networks


Jul 30, 2021
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs

* 17 pages total, 10 page main paper, 5 page appendix, 10 figures total, 8 figures in main paper, 2 figures in appendix 

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A Realistic Simulation Framework for Learning with Label Noise


Jul 23, 2021
Keren Gu, Xander Masotto, Vandana Bachani, Balaji Lakshminarayanan, Jack Nikodem, Dong Yin

* Datasets released at https://github.com/deepmind/deepmind-research/tree/master/noisy_label 

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BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark


Jul 17, 2021
Anand Avati, Martin Seneviratne, Emily Xue, Zhen Xu, Balaji Lakshminarayanan, Andrew M. Dai


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Task-agnostic Continual Learning with Hybrid Probabilistic Models


Jun 24, 2021
Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson, Razvan Pascanu


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A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection


Jun 16, 2021
Jie Ren, Stanislav Fort, Jeremiah Liu, Abhijit Guha Roy, Shreyas Padhy, Balaji Lakshminarayanan


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Predicting Unreliable Predictions by Shattering a Neural Network


Jun 15, 2021
Xu Ji, Razvan Pascanu, Devon Hjelm, Andrea Vedaldi, Balaji Lakshminarayanan, Yoshua Bengio


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Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning


Jun 07, 2021
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran


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Exploring the Limits of Out-of-Distribution Detection


Jun 06, 2021
Stanislav Fort, Jie Ren, Balaji Lakshminarayanan

* S.F. and J.R. contributed equally 

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Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions


Apr 08, 2021
Abhijit Guha Roy, Jie Ren, Shekoofeh Azizi, Aaron Loh, Vivek Natarajan, Basil Mustafa, Nick Pawlowski, Jan Freyberg, Yuan Liu, Zach Beaver, Nam Vo, Peggy Bui, Samantha Winter, Patricia MacWilliams, Greg S. Corrado, Umesh Telang, Yun Liu, Taylan Cemgil, Alan Karthikesalingam, Balaji Lakshminarayanan, Jim Winkens

* Under Review, 19 Pages 

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Combining Ensembles and Data Augmentation can Harm your Calibration


Oct 19, 2020
Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran


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Training independent subnetworks for robust prediction


Oct 13, 2020
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran


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Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift


Jul 17, 2020
Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek


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Bayesian Deep Ensembles via the Neural Tangent Kernel


Jul 11, 2020
Bobby He, Balaji Lakshminarayanan, Yee Whye Teh


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Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks


Jul 10, 2020
Shreyas Padhy, Zachary Nado, Jie Ren, Jeremiah Liu, Jasper Snoek, Balaji Lakshminarayanan


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Density of States Estimation for Out-of-Distribution Detection


Jun 22, 2020
Warren R. Morningstar, Cusuh Ham, Andrew G. Gallagher, Balaji Lakshminarayanan, Alexander A. Alemi, Joshua V. Dillon

* Submitted to NeurIPS. Corrected footnote from: "34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada" to "Preprint. Under review." 

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Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness


Jun 17, 2020
Jeremiah Zhe Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax-Weiss, Balaji Lakshminarayanan


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Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors


May 14, 2020
Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-an Ma, Jasper Snoek, Katherine Heller, Balaji Lakshminarayanan, Dustin Tran

* Code available at https://github.com/google/edward2 

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AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty


Dec 05, 2019
Dan Hendrycks, Norman Mu, Ekin D. Cubuk, Barret Zoph, Justin Gilmer, Balaji Lakshminarayanan

* Code available at https://github.com/google-research/augmix 

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Normalizing Flows for Probabilistic Modeling and Inference


Dec 05, 2019
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, Balaji Lakshminarayanan

* Review article. 60 pages, 4 figures 

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Deep Ensembles: A Loss Landscape Perspective


Dec 05, 2019
Stanislav Fort, Huiyi Hu, Balaji Lakshminarayanan


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Detecting Out-of-Distribution Inputs to Deep Generative Models Using a Test for Typicality


Jun 07, 2019
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Balaji Lakshminarayanan


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Likelihood Ratios for Out-of-Distribution Detection


Jun 07, 2019
Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan


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Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift


Jun 06, 2019
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek


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Hybrid Models with Deep and Invertible Features


Feb 07, 2019
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, Balaji Lakshminarayanan


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Adapting Auxiliary Losses Using Gradient Similarity


Dec 05, 2018
Yunshu Du, Wojciech M. Czarnecki, Siddhant M. Jayakumar, Razvan Pascanu, Balaji Lakshminarayanan


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