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ORCIDN. Siddharth 0001
Siddharth Narayanaswamy
Person information
- affiliation: University of Edinburgh, UK
- affiliation (former): University of Oxford, Department of Engineering Science, UK
- affiliation (PhD 2014): Purdue University, School of Electrical and Computer Engineering, West Lafayette, IN, USA
Other persons with the same name
- N. Siddharth 0002 — Indian Institute of Information Technology, India
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2020 – today
- 2024
[c29]Wanqiu Long, Siddharth Narayanaswamy, Bonnie Webber:
Multi-Label Classification for Implicit Discourse Relation Recognition. ACL (Findings) 2024: 8437-8451- [c28]Alessandro B. Palmarini, Christopher G. Lucas, N. Siddharth:
Bayesian Program Learning by Decompiling Amortized Knowledge. ICML 2024 - [c27]Victor Prokhorov, Ivan Titov, N. Siddharth:
Autoencoding Conditional Neural Processes for Representation Learning. ICML 2024 - [c26]Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina:
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. ICML 2024 - [c25]Mattia Opper, Siddharth Narayanaswamy:
Self-StrAE at SemEval-2024 Task 1: Making Self-Structuring AutoEncoders Learn More With Less. SemEval@NAACL 2024: 108-115 - [i40]Mattia Opper, N. Siddharth:
Self-StrAE at SemEval-2024 Task 1: Making Self-Structuring AutoEncoders Learn More With Less. CoRR abs/2404.01860 (2024) - [i39]Wanqiu Long, N. Siddharth, Bonnie Webber:
Multi-Label Classification for Implicit Discourse Relation Recognition. CoRR abs/2406.04461 (2024) - [i38]Chuanhao Sun, Zhihang Yuan, Kai Xu, Luo Mai, N. Siddharth, Shuo Chen, Mahesh K. Marina:
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding. CoRR abs/2407.09370 (2024) - [i37]Mattia Opper, N. Siddharth:
Banyan: Improved Representation Learning with Explicit Structure. CoRR abs/2407.17771 (2024) - [i36]Mingyue Jian, Siddharth Narayanaswamy:
Are LLMs good pragmatic speakers? CoRR abs/2411.01562 (2024) - 2023
- [c24]Mattia Opper, Victor Prokhorov, Siddharth Narayanaswamy:
StrAE: Autoencoding for Pre-Trained Embeddings using Explicit Structure. EMNLP 2023: 7544-7560 - [i35]Mattia Opper, Victor Prokhorov, N. Siddharth:
StrAE: Autoencoding for Pre-Trained Embeddings using Explicit Structure. CoRR abs/2305.05588 (2023) - [i34]Victor Prokhorov, Ivan Titov, N. Siddharth:
Autoencoding Conditional Neural Processes for Representation Learning. CoRR abs/2305.18485 (2023) - [i33]Alessandro B. Palmarini, Christopher G. Lucas, N. Siddharth:
DreamDecompiler: Improved Bayesian Program Learning by Decompiling Amortised Knowledge. CoRR abs/2306.07856 (2023) - [i32]Mattia Opper, J. Morrison, N. Siddharth:
On the effect of curriculum learning with developmental data for grammar acquisition. CoRR abs/2311.00128 (2023) - 2022
- [c23]Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum:
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. ICLR 2022 - [c22]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy:
Learning Multimodal VAEs through Mutual Supervision. ICLR 2022 - [c21]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, Siddharth Narayanaswamy, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. ICLR 2022 - [c20]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. ICML 2022: 20026-20040 - [c19]Yichao Liang, Josh Tenenbaum, Tuan Anh Le, N. Siddharth:
Drawing out of Distribution with Neuro-Symbolic Generative Models. NeurIPS 2022 - [i31]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. CoRR abs/2201.13100 (2022) - [i30]Yichao Liang, Joshua B. Tenenbaum, Tuan Anh Le, N. Siddharth:
Drawing out of Distribution with Neuro-Symbolic Generative Models. CoRR abs/2206.01829 (2022) - 2021
- [c18]Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, Siddharth Narayanaswamy, Tom Rainforth:
Capturing Label Characteristics in VAEs. ICLR 2021 - [c17]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. ICLR 2021 - [i29]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, N. Siddharth, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. CoRR abs/2104.09937 (2021) - [i28]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon
, N. Siddharth:
Learning Multimodal VAEs through Mutual Supervision. CoRR abs/2106.12570 (2021) - [i27]Ning Miao, Emile Mathieu, N. Siddharth, Yee Whye Teh, Tom Rainforth:
InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents. CoRR abs/2106.13746 (2021) - [i26]Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, N. Siddharth, Samuel J. Gershman, Joshua B. Tenenbaum:
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. CoRR abs/2107.06393 (2021) - 2020
- [j3]Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, Adnane Boukhayma, N. Siddharth, Philip H. S. Torr:
DGPose: Deep Generative Models for Human Body Analysis. Int. J. Comput. Vis. 128(5): 1537-1563 (2020) - [c16]Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N. Siddharth, Wendelin Boehmer, Shimon Whiteson:
Multitask Soft Option Learning. UAI 2020: 969-978 - [i25]Daniela Massiceti, Viveka Kulharia, Puneet K. Dokania, N. Siddharth, Philip H. S. Torr:
A Revised Generative Evaluation of Visual Dialogue. CoRR abs/2004.09272 (2020) - [i24]Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin:
Simulation-Based Inference for Global Health Decisions. CoRR abs/2005.07062 (2020) - [i23]Tom Joy, Sebastian M. Schmon, Philip H. S. Torr, N. Siddharth, Tom Rainforth:
Rethinking Semi-Supervised Learning in VAEs. CoRR abs/2006.10102 (2020) - [i22]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. CoRR abs/2007.01179 (2020)
2010 – 2019
- 2019
- [c15]Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent:
Structured Disentangled Representations. AISTATS 2019: 2525-2534 - [c14]Emile Mathieu, Tom Rainforth, N. Siddharth, Yee Whye Teh:
Disentangling Disentanglement in Variational Autoencoders. ICML 2019: 4402-4412 - [c13]Yuge Shi, Siddharth Narayanaswamy, Brooks Paige, Philip H. S. Torr:
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models. NeurIPS 2019: 15692-15703 - [c12]Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood:
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow. UAI 2019: 1039-1049 - [c11]Rodrigo Andrade de Bem, Arnab Ghosh, Adnane Boukhayma, Thalaiyasingam Ajanthan, N. Siddharth, Philip H. S. Torr:
A Conditional Deep Generative Model of People in Natural Images. WACV 2019: 1449-1458 - [i21]Maximilian Igl, Andrew Gambardella, Nantas Nardelli, N. Siddharth, Wendelin Böhmer, Shimon Whiteson:
Multitask Soft Option Learning. CoRR abs/1904.01033 (2019) - [i20]Yuge Shi, N. Siddharth, Brooks Paige, Philip H. S. Torr:
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models. CoRR abs/1911.03393 (2019) - [i19]Alexander Muryy, N. Siddharth, Nantas Nardelli, Andrew Glennerster, Philip H. S. Torr:
Lessons from reinforcement learning for biological representations of space. CoRR abs/1912.06615 (2019) - 2018
- [c10]Daniela Massiceti, N. Siddharth, Puneet Kumar Dokania, Philip H. S. Torr:
FlipDial: A Generative Model for Two-Way Visual Dialogue. CVPR 2018: 6097-6105 - [c9]Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr:
A Semi-supervised Deep Generative Model for Human Body Analysis. ECCV Workshops (2) 2018: 500-517 - [c8]Stefan Webb, Adam Golinski, Robert Zinkov, Siddharth Narayanaswamy, Tom Rainforth, Yee Whye Teh, Frank Wood:
Faithful Inversion of Generative Models for Effective Amortized Inference. NeurIPS 2018: 3074-3084 - [i18]Daniela Massiceti, N. Siddharth, Puneet Kumar Dokania, Philip H. S. Torr:
FlipDial: A Generative Model for Two-Way Visual Dialogue. CoRR abs/1802.03803 (2018) - [i17]Babak Esmaeili, Hao Wu, Sarthak Jain, N. Siddharth, Brooks Paige, Jan-Willem van de Meent:
Hierarchical Disentangled Representations. CoRR abs/1804.02086 (2018) - [i16]Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr:
DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis. CoRR abs/1804.06364 (2018) - [i15]Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood:
Revisiting Reweighted Wake-Sleep. CoRR abs/1805.10469 (2018) - [i14]Emile Mathieu, Tom Rainforth, Siddharth Narayanaswamy, Yee Whye Teh:
Disentangling Disentanglement. CoRR abs/1812.02833 (2018) - [i13]Daniela Massiceti, Puneet K. Dokania, N. Siddharth, Philip H. S. Torr:
Visual Dialogue without Vision or Dialogue. CoRR abs/1812.06417 (2018) - 2017
- [c7]Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr:
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. NIPS 2017: 5925-5935 - [i12]N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr:
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. CoRR abs/1706.00400 (2017) - [i11]Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Yee Whye Teh, Frank D. Wood:
Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference. CoRR abs/1712.00287 (2017) - 2016
- [j2]Daniel Paul Barrett, Andrei Barbu, N. Siddharth, Jeffrey Mark Siskind:
Saying What You're Looking For: Linguistics Meets Video Search. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 2069-2081 (2016) - [i10]N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr:
Inducing Interpretable Representations with Variational Autoencoders. CoRR abs/1611.07492 (2016) - [i9]Shehroze Bhatti, Alban Desmaison, Ondrej Miksik, Nantas Nardelli, N. Siddharth, Philip H. S. Torr:
Playing Doom with SLAM-Augmented Deep Reinforcement Learning. CoRR abs/1612.00380 (2016) - 2015
- [j1]Haonan Yu, N. Siddharth, Andrei Barbu, Jeffrey Mark Siskind:
A Compositional Framework for Grounding Language Inference, Generation, and Acquisition in Video. J. Artif. Intell. Res. 52: 601-713 (2015) - [i8]Andreas Stuhlmüller, Robert X. D. Hawkins, N. Siddharth, Noah D. Goodman:
Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs. CoRR abs/1509.02962 (2015) - 2014
- [c6]N. Siddharth, Andrei Barbu, Jeffrey Mark Siskind:
Seeing What You're Told: Sentence-Guided Activity Recognition in Video. CVPR 2014: 732-739 - [c5]Andrei Barbu, Daniel Paul Barrett, Wei Chen, Siddharth Narayanaswamy, Caiming Xiong, Jason J. Corso, Christiane D. Fellbaum, Catherine Hanson, Stephen José Hanson, Sébastien Hélie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, Ronnie B. Wilbur:
Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions. ECCV (5) 2014: 612-627 - [i7]Andrei Barbu, Alexander Bridge, Zachary Burchill, Dan Coroian, Sven J. Dickinson, Sanja Fidler, Aaron Michaux, Sam Mussman, Siddharth Narayanaswamy, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell W. Waggoner, Song Wang, Jinlian Wei, Yifan Yin, Zhiqi Zhang:
Video In Sentences Out. CoRR abs/1408.6418 (2014) - 2013
- [c4]Yu Cao, Daniel Paul Barrett, Andrei Barbu, Siddharth Narayanaswamy, Haonan Yu, Aaron Michaux, Yuewei Lin, Sven J. Dickinson, Jeffrey Mark Siskind, Song Wang:
Recognize Human Activities from Partially Observed Videos. CVPR 2013: 2658-2665 - [i6]Siddharth Narayanaswamy, Andrei Barbu, Jeffrey Mark Siskind:
Seeing What You're Told: Sentence-Guided Activity Recognition In Video. CoRR abs/1308.4189 (2013) - [i5]Andrei Barbu, Siddharth Narayanaswamy, Jeffrey Mark Siskind:
Saying What You're Looking For: Linguistics Meets Video Search. CoRR abs/1309.5174 (2013) - 2012
- [c3]Andrei Barbu, Alexander Bridge, Zachary Burchill, Dan Coroian, Sven J. Dickinson, Sanja Fidler, Aaron Michaux, Sam Mussman, Siddharth Narayanaswamy, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell W. Waggoner, Song Wang, Jinlian Wei, Yifan Yin, Zhiqi Zhang:
Video In Sentences Out. UAI 2012: 102-112 - [i4]Andrei Barbu, Aaron Michaux, Siddharth Narayanaswamy, Jeffrey Mark Siskind:
Simultaneous Object Detection, Tracking, and Event Recognition. CoRR abs/1204.2741 (2012) - [i3]Andrei Barbu, Alexander Bridge, Zachary Burchill, Dan Coroian, Sven J. Dickinson, Sanja Fidler, Aaron Michaux, Sam Mussman, Siddharth Narayanaswamy, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell W. Waggoner, Song Wang, Jinlian Wei, Yifan Yin, Zhiqi Zhang:
Video In Sentences Out. CoRR abs/1204.2742 (2012) - [i2]Siddharth Narayanaswamy, Andrei Barbu, Jeffrey Mark Siskind:
Seeing Unseeability to See the Unseeable. CoRR abs/1204.2801 (2012) - [i1]Andrei Barbu, Alexander Bridge, Dan Coroian, Sven J. Dickinson, Sam Mussman, Siddharth Narayanaswamy, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell W. Waggoner, Song Wang, Jinlian Wei, Yifan Yin, Zhiqi Zhang:
Large-Scale Automatic Labeling of Video Events with Verbs Based on Event-Participant Interaction. CoRR abs/1204.3616 (2012) - 2011
- [c2]Siddharth Narayanaswamy, Andrei Barbu, Jeffrey Mark Siskind:
A visual language model for estimating object pose and structure in a generative visual domain. ICRA 2011: 4854-4860 - 2010
- [c1]Andrei Barbu, Siddharth Narayanaswamy, Jeffrey Mark Siskind:
Learning physically-instantiated game play through visual observation. ICRA 2010: 1879-1886
Coauthor Index
Philip Torr 0001
aka: Philip H. S. Torr
aka: Philip H. S. Torr
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