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DARTS without a Validation Set: Optimizing the Marginal Likelihood


Dec 24, 2021
Miroslav Fil, Binxin Ru, Clare Lyle, Yarin Gal

* Presented at the 5th Workshop on Meta-Learning at NeurIPS 2021 

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QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results


Dec 19, 2021
Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat AK, Sarahi Rosas-González, Illyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh McHugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-Andr Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

* Under submission at MELBA journal 

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Decomposing Representations for Deterministic Uncertainty Estimation


Dec 01, 2021
Haiwen Huang, Joost van Amersfoort, Yarin Gal


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DeDUCE: Generating Counterfactual Explanations Efficiently


Nov 29, 2021
Benedikt Höltgen, Lisa Schut, Jan M. Brauner, Yarin Gal

* Presented at the 1st Workshop on eXplainable AI approaches for debugging and diagnosis ([email protected]

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Contrastive Representation Learning with Trainable Augmentation Channel


Nov 15, 2021
Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal


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Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation


Nov 05, 2021
Muhammed Razzak, Gonzalo Mateo-Garcia, Luis Gómez-Chova, Yarin Gal, Freddie Kalaitzis


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Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data


Nov 03, 2021
Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal

* 24 pages, 8 Figures, 5 tables, NeurIPS 2021 

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Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific


Nov 03, 2021
Andrew Jesson, Peter Manshausen, Alyson Douglas, Duncan Watson-Parris, Yarin Gal, Philip Stier


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Deep Deterministic Uncertainty for Semantic Segmentation


Oct 29, 2021
Jishnu Mukhoti, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal


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GeneDisco: A Benchmark for Experimental Design in Drug Discovery


Oct 22, 2021
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab


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Quantifying Uncertainty for Machine Learning Based Diagnostic


Jul 29, 2021
Owen Convery, Lewis Smith, Yarin Gal, Adi Hanuka

* arXiv admin note: substantial text overlap with arXiv:2105.04654 

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Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks


Jul 23, 2021
Andrey Malinin, Neil Band, Ganshin, Alexander, German Chesnokov, Yarin Gal, Mark J. F. Gales, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Roginskiy, Denis, Mariya Shmatova, Panos Tigas, Boris Yangel


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Prioritized training on points that are learnable, worth learning, and not yet learned


Jul 06, 2021
Sören Mindermann, Muhammed Razzak, Winnie Xu, Andreas Kirsch, Mrinank Sharma, Adrien Morisot, Aidan N. Gomez, Sebastian Farquhar, Jan Brauner, Yarin Gal

* ICML 2021 Workshop on Subset Selection in Machine Learning 

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Improving black-box optimization in VAE latent space using decoder uncertainty


Jun 30, 2021
Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal


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A Practical & Unified Notation for Information-Theoretic Quantities in ML


Jun 22, 2021
Andreas Kirsch, Yarin Gal


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A Simple Baseline for Batch Active Learning with Stochastic Acquisition Functions


Jun 22, 2021
Andreas Kirsch, Sebastian Farquhar, Yarin Gal


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Active Learning under Pool Set Distribution Shift and Noisy Data


Jun 22, 2021
Andreas Kirsch, Tom Rainforth, Yarin Gal


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Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective


Jun 17, 2021
Lewis Smith, Joost van Amersfoort, Haiwen Huang, Stephen Roberts, Yarin Gal

* Main paper 10 pages including references, appendix 10 pages. 7 figures and 6 tables including appendix 

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KL Guided Domain Adaptation


Jun 14, 2021
A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atılım Güneş Baydin


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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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Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning


Jun 04, 2021
Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Tom Rainforth, Yarin Gal

* First two authors contributed equally 

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Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization


May 05, 2021
Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa, Farrukh Chishtie, Natalia Díaz-Rodríguez, Océane Boulais, Aruna Sankaranarayanan, Aaron Piña, Yarin Gal, Chedy Raïssi, Alexander Lavin, Dava Newman

* arXiv admin note: text overlap with arXiv:2010.08103 

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Outcome-Driven Reinforcement Learning via Variational Inference


Apr 20, 2021
Tim G. J. Rudner, Vitchyr H. Pong, Rowan McAllister, Yarin Gal, Sergey Levine


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Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties


Mar 16, 2021
Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal

* Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 
* 21 pages, 13 Figures 

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Robustness to Pruning Predicts Generalization in Deep Neural Networks


Mar 10, 2021
Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal


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Active Testing: Sample-Efficient Model Evaluation


Mar 09, 2021
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth


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