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Yarin Gal
Semi-supervised Learning of Galaxy Morphology using Equivariant Transformer Variational Autoencoders

Nov 17, 2020
Mizu Nishikawa-Toomey, Lewis Smith, Yarin Gal

* Accepted at the workshop for Machine Learning and the Physical Sciences, 34th Conference on Neural Information Processing Systems (NeurIPS) December 11, 2020 
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On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes

Nov 01, 2020
Tim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth


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Inter-domain Deep Gaussian Processes

Nov 01, 2020
Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal

* Published in Proceedings of the 37th International Conference on Machine Learning (ICML 2020) 
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A Bayesian Perspective on Training Speed and Model Selection

Oct 27, 2020
Clare Lyle, Lisa Schut, Binxin Ru, Yarin Gal, Mark van der Wilk

* To be presented at NeurIPS 2020 
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Physics-informed GANs for Coastal Flood Visualization

Oct 16, 2020
Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa, Farrukh Chishtie, Natalia Díaz-Rodriguez, Océane Boulais, Aaron Piña, Dava Newman, Alexander Lavin, Yarin Gal, Chedy Raïssi

* Under Review 
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Interlocking Backpropagation: Improving depthwise model-parallelism

Oct 08, 2020
Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal


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On the robustness of effectiveness estimation of nonpharmaceutical interventions against COVID-19 transmission

Jul 27, 2020
Mrinank Sharma, Sören Mindermann, Jan Markus Brauner, Gavin Leech, Anna B. Stephenson, Tomáš Gavenčiak, Jan Kulveit, Yee Whye Teh, Leonid Chindelevitch, Yarin Gal


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SliceOut: Training Transformers and CNNs faster while using less memory

Jul 21, 2020
Pascal Notin, Aidan N. Gomez, Joanna Yoo, Yarin Gal


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Single Shot Structured Pruning Before Training

Jul 01, 2020
Joost van Amersfoort, Milad Alizadeh, Sebastian Farquhar, Nicholas Lane, Yarin Gal


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Identifying Causal Effect Inference Failure with Uncertainty-Aware Models

Jul 01, 2020
Andrew Jesson, Sören Mindermann, Uri Shalit, Yarin Gal


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Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Jun 26, 2020
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

* Camera-ready version, International Conference of Machine Learning 2020 
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Learning Invariant Representations for Reinforcement Learning without Reconstruction

Jun 18, 2020
Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine


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Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers

Jun 08, 2020
Tim Z. Xiao, Aidan N. Gomez, Yarin Gal

* 19 pages, 9 figures 
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Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search

Jun 08, 2020
Binxin Ru, Clare Lyle, Lisa Schut, Mark van der Wilk, Yarin Gal

* 14 pages, 10 figures 
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Uncertainty Evaluation Metric for Brain Tumour Segmentation

May 28, 2020
Raghav Mehta, Angelos Filos, Yarin Gal, Tal Arbel


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On the Benefits of Invariance in Neural Networks

May 01, 2020
Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, Benjamin Bloem-Reddy


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Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning

Apr 09, 2020
Andreas Kirsch, Clare Lyle, Yarin Gal


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Capsule Networks -- A Probabilistic Perspective

Apr 07, 2020
Lewis Smith, Lisa Schut, Yarin Gal, Mark van der Wilk


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Baryons from Mesons: A Machine Learning Perspective

Mar 23, 2020
Yarin Gal, Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra

* 25 pages, 3 figures, 1 table 
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Invariant Causal Prediction for Block MDPs

Mar 12, 2020
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup

* 16 pages, 8 figures 
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Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network

Mar 04, 2020
Joost van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal


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Try Depth Instead of Weight Correlations: Mean-field is a Less Restrictive Assumption for Deeper Networks

Feb 10, 2020
Sebastian Farquhar, Lewis Smith, Yarin Gal


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A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks

Dec 22, 2019
Angelos Filos, Sebastian Farquhar, Aidan N. Gomez, Tim G. J. Rudner, Zachary Kenton, Lewis Smith, Milad Alizadeh, Arnoud de Kroon, Yarin Gal


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Adversarial recovery of agent rewards from latent spaces of the limit order book

Dec 09, 2019
Jacobo Roa-Vicens, Yuanbo Wang, Virgile Mison, Yarin Gal, Ricardo Silva

* Published as a workshop paper on NeurIPS 2019 Workshop on Robust AI in Financial Services. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada 
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Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning

Nov 10, 2019
Brad Neuberg, Souvik Bose, Valentina Salvatelli, Luiz F. G. dos Santos, Mark Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin

* 6 pages, 3 figures, Accepted at NeurIPS 2019 Workshop ML4PS 
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Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona

Nov 10, 2019
Valentina Salvatelli, Souvik Bose, Brad Neuberg, Luiz F. G. dos Santos, Mark Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin

* 5 pages, 6 figures, Accepted at the NeurIPS 2019 Workshop ML4PS 
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Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics \& Losses

Nov 04, 2019
Anna Jungbluth, Xavier Gitiaux, Shane A. Maloney, Carl Shneider, Paul J. Wright, Alfredo Kalaitzis, Michel Deudon, Atılım Güneş Baydin, Yarin Gal, Andrés Muñoz-Jaramillo


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Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties

Nov 04, 2019
Xavier Gitiaux, Shane A. Maloney, Anna Jungbluth, Carl Shneider, Paul J. Wright, Atılım Güneş Baydin, Michel Deudon, Yarin Gal, Alfredo Kalaitzis, Andrés Muñoz-Jaramillo


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VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Oct 18, 2019
Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson


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