Suivre
N. Siddharth
N. Siddharth
Reader in Explainable AI, University of Edinburgh
Adresse e-mail validée de iffsid.com - Page d'accueil
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Learning disentangled representations with semi-supervised deep generative models
N Siddharth, B Paige, JW Van de Meent, A Desmaison, N Goodman, ...
428*2018
Disentangling Disentanglement in Variational Autoencoders
E Mathieu, T Rainforth, N Siddharth, YW Teh
International Conference on Machine Learning, 4402-4412, 2019
3532019
Variational mixture-of-experts autoencoders for multi-modal deep generative models
Y Shi, N Siddharth, B Paige, PHS Torr
Advances in Neural Information Processing Systems, 2019
3232019
Gradient matching for domain generalization
Y Shi, J Seely, PHS Torr, N Siddharth, A Hannun, N Usunier, G Synnaeve
arXiv preprint arXiv:2104.09937, 2021
3182021
Recognize human activities from partially observed videos
Y Cao, D Barrett, A Barbu, N Siddharth, H Yu, A Michaux, Y Lin, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
2442013
Structured disentangled representations
B Esmaeili, H Wu, S Jain, A Bozkurt, N Siddharth, B Paige, DH Brooks, ...
Proceedings of the 22nd International Conference on Artificial Intelligence …, 2018
2142018
Video In Sentences Out
A Barbu, A Bridge, Z Burchill, D Coroian, S Dickinson, S Fidler, A Michaux, ...
UAI, 102-112, 2012
2092012
Adversarial masking for self-supervised learning
Y Shi, N Siddharth, P Torr, AR Kosiorek
International Conference on Machine Learning, 20026-20040, 2022
1002022
Playing doom with slam-augmented deep reinforcement learning
S Bhatti, A Desmaison, O Miksik, N Nardelli, N Siddharth, PHS Torr
arXiv preprint arXiv:1612.00380, 2016
992016
Revisiting reweighted wake-sleep for models with stochastic control flow
TA Le, AR Kosiorek, N Siddharth, YW Teh, F Wood
Uncertainty in Artificial Intelligence, 1039-1049, 2020
77*2020
Capturing label characteristics in VAEs
T Joy, SM Schmon, PHS Torr, N Siddharth, T Rainforth
International Conference On Learning Representations, 2021
59*2021
Faithful inversion of generative models for effective amortized inference
S Webb, A Golinski, R Zinkov, N Siddharth, T Rainforth, YW Teh, F Wood
Advances in Neural Information Processing Systems, 3074-3084, 2018
532018
Seeing What You’re Told: Sentence-Guided Activity Recognition in Video
N Siddharth, A Barbu, JM Siskind
Proceedings of the 27th IEEE Conference on Computer Vision and Pattern …, 2014
52*2014
A compositional framework for grounding language inference, generation, and acquisition in video
H Yu, N Siddharth, A Barbu, JM Siskind
Journal of Artificial Intelligence Research 52, 601-713, 2015
492015
FlipDial: A generative model for two-way visual dialogue
D Massiceti, N Siddharth, PK Dokania, PHS Torr
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018
482018
Relating by contrasting: A data-efficient framework for multimodal DGMs
Y Shi, B Paige, PHS Torr, N Siddharth
Open Review, 2021
45*2021
Correlating videos and sentences
JM Siskind, A Barbu, N Siddharth, H Yu
US Patent 9,183,466, 2015
432015
Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions
A Barbu, DP Barrett, W Chen, N Siddharth, C Xiong, JJ Corso, ...
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
412014
Visual dialogue without vision or dialogue
D Massiceti, PK Dokania, N Siddharth, PHS Torr
arXiv preprint arXiv:1812.06417, 2018
322018
Multitask Soft Option Learning
M Igl, A Gambardella, J He, N Nardelli, N Siddharth, W Böhmer, ...
arXiv preprint arXiv:1904.01033, 2019
312019
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