Follow
Joost van Amersfoort
Joost van Amersfoort
Verified email at cs.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning
A Kirsch, J van Amersfoort, Y Gal
NeurIPS 2019, 2019
2812019
Variational Recurrent Auto-Encoders
O Fabius, J van Amersfoort
ICLR 2015 Workshop, 2014
2752014
Uncertainty estimation using a single deep deterministic neural network
J van Amersfoort, L Smith, YW Teh, Y Gal
International Conference on Machine Learning, 2020
192*2020
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
642017
On feature collapse and deep kernel learning for single forward pass uncertainty
J van Amersfoort, L Smith, A Jesson, O Key, Y Gal
arXiv preprint arXiv:2102.11409, 2021
55*2021
Deterministic Neural Networks with Inductive Biases Capture Epistemic and Aleatoric Uncertainty
J Mukhoti, A Kirsch, J van Amersfoort, PHS Torr, Y Gal
arXiv preprint arXiv:2102.11582, 2021
502021
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
402017
Single shot structured pruning before training
J van Amersfoort, M Alizadeh, S Farquhar, N Lane, Y Gal
arXiv preprint arXiv:2007.00389, 2020
112020
Deep hashing using entropy regularised product quantisation network
J Schlemper, J Caballero, A Aitken, J van Amersfoort
arXiv preprint arXiv:1902.03876, 2019
52019
Prospect pruning: Finding trainable weights at initialization using meta-gradients
M Alizadeh, SA Tailor, LM Zintgraf, J van Amersfoort, S Farquhar, ...
arXiv preprint arXiv:2202.08132, 2022
42022
Causal-BALD: Deep Bayesian active learning of outcomes to infer treatment-effects from observational data
A Jesson, P Tigas, J van Amersfoort, A Kirsch, U Shalit, Y Gal
Advances in Neural Information Processing Systems 34, 30465-30478, 2021
42021
Deep Deterministic Uncertainty for Semantic Segmentation
J Mukhoti, J van Amersfoort, PHS Torr, Y Gal
arXiv preprint arXiv:2111.00079, 2021
42021
Plex: Towards reliability using pretrained large model extensions
D Tran, J Liu, MW Dusenberry, D Phan, M Collier, J Ren, K Han, Z Wang, ...
arXiv preprint arXiv:2207.07411, 2022
32022
Decomposing Representations for Deterministic Uncertainty Estimation
H Huang, J van Amersfoort, Y Gal
arXiv preprint arXiv:2112.00856, 2021
12021
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
12021
Mixtures of large-scale dynamic functional brain network modes
C Gohil, E Roberts, R Timms, A Skates, C Higgins, A Quinn, U Pervaiz, ...
bioRxiv, 2022
2022
Frame interpolation with multi-scale deep loss functions and generative adversarial networks
J Van Amersfoort, W Shi, J Caballero, AAA Diaz, F Massa, J Totz, Z Wang
US Patent 11,122,238, 2021
2021
On the Usage of Herding in Learning Sigmoid Belief Networks
JR van Amersfoort
2016
The system can't perform the operation now. Try again later.
Articles 1–18