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N. Siddharth
N. Siddharth
Reader in Explainable AI, University of Edinburgh
Zweryfikowany adres z iffsid.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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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, ...
392*2018
Disentangling Disentanglement in Variational Autoencoders
E Mathieu, T Rainforth, N Siddharth, YW Teh
International Conference on Machine Learning, 4402-4412, 2019
2782019
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
2262013
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
1982019
Video In Sentences Out
A Barbu, A Bridge, Z Burchill, D Coroian, S Dickinson, S Fidler, A Michaux, ...
UAI, 102-112, 2012
1942012
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
1852021
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
177*2018
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
892016
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
65*2020
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
50*2014
Adversarial masking for self-supervised learning
Y Shi, N Siddharth, P Torr, AR Kosiorek
International Conference on Machine Learning, 20026-20040, 2022
482022
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
472018
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
452015
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
422018
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
Capturing label characteristics in VAEs
T Joy, SM Schmon, PHS Torr, N Siddharth, T Rainforth
International Conference On Learning Representations, 2021
36*2021
Correlating videos and sentences
JM Siskind, A Barbu, N Siddharth, H Yu
US Patent 9,183,466, 2015
332015
Simultaneous Object Detection, Tracking, and Event Recognition
A Barbu, N Siddharth, A Michaux, JM Siskind
Advances in Cognitive Systems 2, 203-220, 2012
292012
Learning physically-instantiated game play through visual observation
A Barbu, N Siddharth, JM Siskind
Robotics and Automation (ICRA), 2010 IEEE International Conference on, 1879-1886, 2010
292010
Relating by contrasting: A data-efficient framework for multimodal DGMs
Y Shi, B Paige, PHS Torr, N Siddharth
Open Review, 2021
28*2021
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