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Maximilian Igl, Andrew Gambardella, Nantas Nardelli, N. Siddharth, Wendelin Böhmer, and Shimon Whiteson.
Multitask Soft Option Learning.
In Uncertainty In Artificial Intelligence (UAI). August. 2020.

Yuge Shi, Brooks Paige, Philip H. S. Torr, and N. Siddharth.
Relating By Contrasting: A Data-Efficient Framework For Multimodal Generative Models.
ArXiv e-prints:arXiv:2007.01179, July. 2020.

Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, N. Siddharth*, and Tom Rainforth*.
Rethinking Semi-Supervised Learning In Vaes.
ArXiv e-prints:arXiv:2006.10102, June. 2020.

Yuge Shi*, N. Siddharth*, Brooks Paige, and Philip H. S. Torr.
Variational Mixture-Of-Experts Autoencoders For Multi-Modal Deep Generative Models.
In Advances In Neural Information Processing Systems (NeurIPS), pages 15692–15703. December. 2019.

Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, and Frank Wood.
Revisiting Reweighted Wake-Sleep For Models With Stochastic Control Flow.
In Uncertainty In Artificial Intelligence (UAI). July. 2019.

Emile Mathieu*, Tom Rainforth*, N Siddharth*, and Yee Whye Teh.
Disentangling Disentanglement In Variational Autoencoders.
In Kamalika Chaudhuri and Ruslan Salakhutdinov, editors, International Conference On Machine Learning (ICML), volume 97, pages 4402–4412, Long Beach, California, USA, June. PMLR. 2019.

Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N Siddharth, Brooks Paige, Dana H. Brooks, Jennifer Dy, and Jan-Willem van de Meent.
Structured Disentangled Representations.
In Kamalika Chaudhuri and Masashi Sugiyama, editors, International Conference On Artificial Intelligence And Statistics (AISTATS), volume 89, pages 2525–2534. PMLR, April. 2019.

Rodrigo De Bem, Arnab Ghosh, Adnane Boukhayma, Thalaiyasingam Ajanthan, N Siddharth*, and Philip Torr*.
A Conditional Deep Generative Model Of People In Natural Images.
In Winter Conference On Applications Of Computer Vision (WACV), pages 1449–1458. January. 2019.

Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Tom Rainforth, Yee Whye Teh, and Frank Wood.
Faithful Inversion Of Generative Models For Effective Amortized Inference.
In Advances In Neural Information Processing Systems (NeurIPS), pages 3074–3084. December. 2018.

Daniela Massiceti, N. Siddharth, Puneet K. Dokania, and Philip H. S. Torr.
FlipDIal: A Generative Model For Two-Way Visual Dialogue.
In Proceedings Of The Ieee Conference On Computer Vision And Pattern Recognition (CVPR), pages 6097–6105. June. 2018.

N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank Wood, and Philip H. S. Torr.
Learning Disentangled Representations With Semi-Supervised Deep Generative Models.
In Advances In Neural Information Processing Systems (NeurIPS), pages 5927–5937. December. 2017.

Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth*, and Philip H. S. Torr*.
Playing Doom With Slam-Augmented Deep Reinforcement Learning.
ArXiv e-prints, December. 2016.

Andrei Barbu, N. Siddharth, Haonan Yu, and Jeffrey Mark Siskind.
Correlating Videos And Sentences.
U.S. patent, 9183466, November. 2015.

Andreas Stuhlmüller, Robert X. D. Hawkins, N. Siddharth, and Noah D. Goodman.
Coarse-To-Fine Sequential Monte Carlo For Probabilistic Programs.
ArXiv e-prints, September. 2015.

Andrei Barbu*, Daniel P. Barrett*, Wei Chen, N. Siddharth*, Caiming Xiong, Jason J. Corso, Cristiane D. Fellbaum, Stephen Jose Hanson Catherine Hanson, Sebastien Helie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, and Ronnie B. Wilbur.
Seeing Is Worse Than Believing: Reading People’S Minds Better Than Computer-Vision Methods Recognize Actions.
In Proceedings Of The European Conference On Computer Vision (ECCV), pages 612–627, Zurich, Switzerland, September. 2014a.

N. Siddharth*, Andrei Barbu*, and Jeffrey Mark Siskind.
Seeing What You’Re Told: Sentence-Guided Activity Recognition In Video.
In Proceedings Of The Ieee Conference On Computer Vision And Pattern Recognition (CVPR), pages 732–739, Columbus, OH, June. 2014.

Yu Cao, Daniel P. Barrett, Andrei Barbu, N. Siddharth, Haonan Yu, Aaron Michaux, Yuwei Lin, Sven Dickinson, Jeffrey Mark Siskind, and Song Wang.
Recognizing Human Activities From Partially Observed Videos.
In Proceedings Of The Ieee Conference On Computer Vision And Pattern Recognition (CVPR), pages 2658–2665, Portland, OR, June. 2013.

Andrei Barbu*, N. Siddharth*, Caiming Xiong, Jason J. Corso, Christiane D. Fellbaum, Catherine Hanson, Stephen Jose Hason, Sebastien Helie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, and Ronnie B. Wilbur.
The Compositional Nature Of Verb And Argument Representations In The Human Brain.
ArXiv e-prints, June. 2013.

Andrei Barbu*, Alexander Bridge, Zach Burchill, Dan Coroian, Sven Dickinson, Sanja Fidler, Aaron Michaux, Sam Mussman, N. Siddharth*, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell Waggoner, Song Wang, Jinlian Wei, Yifan Yin, and Zhiqi Zhang.
Video In Sentences Out.
In Proceedings Of The Twenty-Eighth Conference On Uncertainty In Artificial Intelligence (UAI), pages 102–112, Catalina Island, CA, August. 2012a.

Andrei Barbu*, Alexander Bridge, Dan Coroian, Sven Dickinson, Sam Mussman, N. Siddharth*, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell Waggoner, Song Wang, Jinlian Wei, Yifan Yin, and Zhiqi Zhang.
Large-Scale Automatic Labeling Of Video Events With Verbs Based On Event-Participant Interaction.
ArXiv e-prints, April. 2012b.

N. Siddharth*, Andrei Barbu*, and Jeffrey Mark Siskind.
A Visual Language Model For Estimating Object Pose And Structure In A Generative Visual Domain.
In Proceedings Of The Ieee International Conference On Robotics And Automation (ICRA), pages 4854–4860, Shanghai, China, May. 2011.

Andrei Barbu*, N. Siddharth*, and Jeffrey Mark Siskind.
Learning Physically-Instantiated Game Play Through Visual Observation.
In Proceedings Of The Ieee International Conference On Robotics And Automation (ICRA), pages 1879–1886, Anchorage, AK, May. 2010.

Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, Adnane Boukhayma, N. Siddharth*, and Philip H. S. Torr*.
DGPose: DEep GEnerative MOdels For HUman BOdy ANalysis.
International Journal of Computer Vision (IJCV), 128(5):1537–1563. 2020.

N. Siddharth and Brooks Paige.
Learning Generative Models From Classifier Uncertainties.
In ICML Workshop On UNcertainty & RObustness In DEep LEarning. 2020.

Alex Muryy, N. Siddharth, Nantas Nardelli, Andrew Glennerster, and Philip H. S. Torr.
Lessons From Reinforcement Learning For Biological Representations Of Space.
Vision Research (VR), 174:79–93. 2020.

Christian Schroeder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Rob Zinkov, Puneet Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, and Philip H. S. Torr.
Simulation-Based Inference For Global Health Decisions.
In ICML Workshop On Ml For Global Health. 2020.

Rodrigo de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth*, and Philip H. S. Torr*.
A Semi-Supervised Deep Generative Model For Human Body Analysis.
In ECCV Workshop On HUman BEhaviour UNderstanding. 2018.

Emile Mathieu*, Tom Rainforth*, N. Siddharth*, and Yee Whye Teh.
Disentangling Disentanglement.
In NeurIPS Workshop On BAyesian DEep LEarning. 2018.

Maximilian Igl, Wendelin Boehmer, Andrew Gambardella, Philip H. S. Torr, Nantas Nardelli, N. Siddharth, and Shimon Whiteson.
Inference And Distillation For Option Learning.
In NeurIPS Workshop On INfer To COntrol. 2018.

Daniela Massiceti*, Puneet K. Dokania*, N. Siddharth*, and Philip H. S. Torr.
Visual Dialogue Without Vision Or Dialogue.
In NeurIPS Workshop On CRitiquing And COrrecting TRends In MAchine LEarning. 2018.

N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank Wood, and Philip H. S. Torr.
Inducing Interpretable Representations With Variational Autoencoders.
In NIPS Workshop On INterpretable MAchine LEarning In COmplex SYstems. 2016.

Daniel P. Barrett*, Andrei Barbu*, N. Siddharth*, and Jeffrey Mark Siskind.
Saying What You’Re Looking For: Linguistics Meets Video Search.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 38(10):2069–2081. 2016.

Haonan Yu*, N. Siddharth*, Andrei Barbu*, and Jeffrey Mark Siskind.
A Compositional Framework For Grounding Language Inference, Generation, And Acquisition In Video.
Journal of Artificial Intelligence Research (JAIR), 52:601–713. 2015.

N. Siddharth and Noah D. Goodman.
Informative Scene Descriptions.
In CVPR Workshop On LAnguage And VIsion. 2014.

Andrei Barbu*, N. Siddharth*, and Jeffrey Mark Siskind.
Language-Driven Video Retrieval.
In CVPR Workshop On VIsion MEets COgnition. 2014b.

N. Siddharth*, Andrei Barbu*, and Jeffrey Mark Siskind.
Seeing Unseeability To See The Unseeable.
Advances in Cognitive Systems (ACS), 2:77–94. 2012.

Andrei Barbu*, N. Siddharth*, Aaron Michaux, and Jeffrey Mark Siskind.
Simultaneous Object Detection, Tracking, And Event Recognition.
Advances in Cognitive Systems (ACS), 2:203–220. 2012c.

N. Siddharth, Muniyandi Manivannan, Suresh Devasahayam, and George Mathew.
Design Of A Do-It-Yourself Vr Based Laparoscopic Simulator.
In Medicine Meets Virtual Reality (MMVR). 2009.