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ORCIDYarin Gal
Publications
- 2023
[c69]Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deep Deterministic Uncertainty: A New Simple Baseline. CVPR 2023: 24384-24394- 2022
- [j6]Chetan Gohil, Evan Roberts, Ryan C. Timms, Alex Skates, Cameron Higgins
, Andrew Quinn, Usama Pervaiz, Joost van Amersfoort, Pascal Notin, Yarin Gal, Stanislaw Adaszewski, Mark W. Woolrich:
Mixtures of large-scale dynamic functional brain network modes. NeuroImage 263: 119595 (2022) - [c62]Milad Alizadeh, Shyam A. Tailor, Luisa M. Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal:
Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. ICLR 2022 - [i112]Milad Alizadeh, Shyam A. Tailor, Luisa M. Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal:
Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. CoRR abs/2202.08132 (2022) - [i104]Dustin Tran, Jeremiah Z. 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:
Plex: Towards Reliability using Pretrained Large Model Extensions. CoRR abs/2207.07411 (2022) - 2021
- [c43]Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal:
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data. NeurIPS 2021: 30465-30478 - [i92]Joost van Amersfoort, Lewis Smith, Andrew Jesson, Oscar Key, Yarin Gal:
Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression. CoRR abs/2102.11409 (2021) - [i91]Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty. CoRR abs/2102.11582 (2021) - [i83]Lewis Smith, Joost van Amersfoort, Haiwen Huang, Stephen J. Roberts, Yarin Gal:
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. CoRR abs/2106.02469 (2021) - [i70]Jishnu Mukhoti, Joost van Amersfoort, Philip H. S. Torr, Yarin Gal:
Deep Deterministic Uncertainty for Semantic Segmentation. CoRR abs/2111.00079 (2021) - [i69]Andrew Jesson, Panagiotis Tigas, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal:
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data. CoRR abs/2111.02275 (2021) - [i65]Haiwen Huang, Joost van Amersfoort, Yarin Gal:
Decomposing Representations for Deterministic Uncertainty Estimation. CoRR abs/2112.00856 (2021) - 2020
- [c29]Joost van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal:
Uncertainty Estimation Using a Single Deep Deterministic Neural Network. ICML 2020: 9690-9700 - [i61]Joost van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal:
Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network. CoRR abs/2003.02037 (2020) - [i49]Joost van Amersfoort, Milad Alizadeh, Sebastian Farquhar, Nicholas D. Lane, Yarin Gal:
Single Shot Structured Pruning Before Training. CoRR abs/2007.00389 (2020) - 2019
- [c19]Andreas Kirsch, Joost van Amersfoort, Yarin Gal:
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning. NeurIPS 2019: 7024-7035 - [i32]Andreas Kirsch, Joost van Amersfoort, Yarin Gal:
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning. CoRR abs/1906.08158 (2019)
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