עקוב אחר
Yarin Gal
Yarin Gal
Associate Professor, University of Oxford
כתובת אימייל מאומתת בדומיין cs.ox.ac.uk - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Dropout as a Bayesian approximation: Representing model uncertainty in deep learning‏
Y Gal, Z Ghahramani‏
Proceedings of the 33rd International Conference on Machine Learning (ICML-16), 2015‏
108322015
What uncertainties do we need in Bayesian deep learning for computer vision?‏
A Kendall, Y Gal‏
Advances in neural information processing systems, 5574-5584, 2017‏
56102017
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics‏
A Kendall, Y Gal, R Cipolla‏
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018‏
36032018
Uncertainty in Deep Learning‏
Y Gal‏
University of Cambridge, 2016‏
20912016
A theoretically grounded application of dropout in recurrent neural networks‏
Y Gal, Z Ghahramani‏
Advances in neural information processing systems 29, 1019-1027, 2016‏
20622016
Deep Bayesian Active Learning with Image Data‏
Y Gal, R Islam, Z Ghahramani‏
International Conference on Machine Learning (ICML), 1183-1192, 2017‏
19642017
Inferring the effectiveness of government interventions against COVID-19‏
JM Brauner, S Mindermann, M Sharma, D Johnston, J Salvatier, ...‏
Science 371 (6531), eabd9338, 2021‏
10282021
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference‏
Y Gal, Z Ghahramani‏
4th International Conference on Learning Representations (ICLR) workshop track, 2015‏
9512015
Concrete dropout‏
Y Gal, J Hron, A Kendall‏
Advances in Neural Information Processing Systems, 3581-3590, 2017‏
7372017
Real time image saliency for black box classifiers‏
P Dabkowski, Y Gal‏
Advances in Neural Information Processing Systems, 6967-6976, 2017‏
7162017
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning‏
A Kirsch, J van Amersfoort, Y Gal‏
Advances in Neural Information Processing Systems, 2019, 2019‏
6442019
Uncertainty estimation using a single deep deterministic neural network‏
J van Amersfoort, L Smith, YW Teh, Y Gal‏
International Conference on Machine Learning (ICML), 2020‏
5082020
Disease variant prediction with deep generative models of evolutionary data‏
J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks‏
Nature 599 (7883), 91-95, 2021‏
4882021
Learning Invariant Representations for Reinforcement Learning without Reconstruction‏
A Zhang, R McAllister, R Calandra, Y Gal, S Levine‏
International Conference on Learning Representations (ICLR), 2020‏
4812020
Understanding Measures of Uncertainty for Adversarial Example Detection‏
L Smith, Y Gal‏
Uncertainty in Artificial Intelligence (UAI), 2018‏
4052018
Concrete problems for autonomous vehicle safety: Advantages of Bayesian deep learning‏
R McAllister, Y Gal, A Kendall, M van der Wilk, A Shah, R Cipolla, ...‏
International Joint Conferences on Artificial Intelligence (IJCAI), 2017‏
401*2017
Towards Robust Evaluations of Continual Learning‏
S Farquhar, Y Gal‏
Lifelong Learning: A Reinforcement Learning Approach workshop, ICML, 2018, 2018‏
3222018
Improving PILCO with Bayesian neural network dynamics models‏
Y Gal, R McAllister, CE Rasmussen‏
Data-Efficient Machine Learning workshop, ICML, 2016‏
3162016
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam‏
ME Khan, D Nielsen, V Tangkaratt, W Lin, Y Gal, A Srivastava‏
ICML, 2018, 2018‏
3072018
VariBAD: a very good method for Bayes-adaptive deep RL via meta-learning‏
L Zintgraf, K Shiarlis, M Igl, S Schulze, Y Gal, K Hofmann, S Whiteson‏
International Conference on Learning Representations (ICLR), 2020‏
2762020
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מאמרים 1–20