Joost van Amersfoort
Joost van Amersfoort
Verified email at cs.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
Variational Recurrent Auto-Encoders
O Fabius, J van Amersfoort
ICLR 2015 Workshop, 2014
2062014
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
A Kirsch, J van Amersfoort, Y Gal
NeurIPS 2019, 2019
932019
Transformation-based models of video sequences
J van Amersfoort, A Kannan, MA Ranzato, A Szlam, D Tran, S Chintala
arXiv preprint arXiv:1701.08435, 2017
482017
Uncertainty estimation using a single deep deterministic neural network
J van Amersfoort, L Smith, YW Teh, Y Gal
International Conference on Machine Learning, 2020
36*2020
Frame interpolation with multi-scale deep loss functions and generative adversarial networks
J van Amersfoort, W Shi, A Acosta, F Massa, J Totz, Z Wang, J Caballero
arXiv preprint arXiv:1711.06045, 2017
352017
Deterministic neural networks with appropriate inductive biases capture epistemic and aleatoric uncertainty
J Mukhoti, A Kirsch, J van Amersfoort, PHS Torr, Y Gal
arXiv preprint arXiv:2102.11582, 2021
32021
Improving deterministic uncertainty estimation in deep learning for classification and regression
J van Amersfoort, L Smith, A Jesson, O Key, Y Gal
arXiv preprint arXiv:2102.11409, 2021
32021
Deep hashing using entropy regularised product quantisation network
J Schlemper, J Caballero, A Aitken, J van Amersfoort
arXiv preprint arXiv:1902.03876, 2019
22019
Single Shot Structured Pruning Before Training
J van Amersfoort, M Alizadeh, S Farquhar, N Lane, Y Gal
arXiv preprint arXiv:2007.00389, 2020
12020
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective
L Smith, J van Amersfoort, H Huang, S Roberts, Y Gal
arXiv preprint arXiv:2106.02469, 2021
2021
On the Usage of Herding in Learning Sigmoid Belief Networks
JR van Amersfoort
2016
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Articles 1–11