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Plex: Towards Reliability using Pretrained Large Model Extensions


Jul 15, 2022
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

* Code available at https://goo.gle/plex-code 

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A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness


May 01, 2022
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zack Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan

* arXiv admin note: text overlap with arXiv:2006.10108 

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Reliable Graph Neural Networks for Drug Discovery Under Distributional Shift


Nov 25, 2021
Kehang Han, Balaji Lakshminarayanan, Jeremiah Liu

* 5 page main body, 5 page appendix. Accepted by NeurIPS DistShift Workshop 2021 

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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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