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Shawn Tan
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2020 – today
- 2024
- [i13]Shawn Tan, Yikang Shen, Rameswar Panda, Aaron C. Courville:
Scattered Mixture-of-Experts Implementation. CoRR abs/2403.08245 (2024) - 2023
- [c15]Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan:
Sparse Universal Transformer. EMNLP 2023: 169-179 - [c14]Kian Eng Ong, Sivaji Retta, Ramarajulu Srinivasan, Shawn Tan, Jun Liu:
CattleEyeView: A Multi-task Top-down View Cattle Dataset for Smarter Precision Livestock Farming. VCIP 2023: 1-5 - [i12]Yikang Shen, Zheyu Zhang, Tianyou Cao, Shawn Tan, Zhenfang Chen, Chuang Gan:
ModuleFormer: Learning Modular Large Language Models From Uncurated Data. CoRR abs/2306.04640 (2023) - [i11]Shawn Tan, Yikang Shen, Zhenfang Chen, Aaron C. Courville, Chuang Gan:
Sparse Universal Transformer. CoRR abs/2310.07096 (2023) - [i10]Kian Eng Ong, Sivaji Retta, Ramarajulu Srinivasan, Shawn Tan, Jun Liu:
CattleEyeView: A Multi-task Top-down View Cattle Dataset for Smarter Precision Livestock Farming. CoRR abs/2312.08764 (2023) - 2022
- [c13]Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie Zhou, Aaron C. Courville:
Unsupervised Dependency Graph Network. ACL (1) 2022: 4767-4784 - [c12]Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville:
Learning to Dequantise with Truncated Flows. ICLR 2022 - 2021
- [c11]Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville:
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle. NAACL-HLT 2021: 1660-1672 - 2020
- [c10]Samantha Stranc, Shawn Tan, Kasia Muldner:
Scanpaths distinguish problem format in a math cognition task. CogSci 2020 - [c9]Shawn Tan, Yikang Shen, Alessandro Sordoni, Aaron C. Courville, Timothy J. O'Donnell:
Recursive Top-Down Production for Sentence Generation with Latent Trees. EMNLP (Findings) 2020: 2291-2307 - [i9]Shawn Tan, Yikang Shen, Timothy J. O'Donnell, Alessandro Sordoni, Aaron C. Courville:
Recursive Top-Down Production for Sentence Generation with Latent Trees. CoRR abs/2010.04704 (2020) - [i8]Yikang Shen, Shawn Tan, Alessandro Sordoni, Siva Reddy, Aaron C. Courville:
Explicitly Modeling Syntax in Language Model improves Generalization. CoRR abs/2011.07960 (2020)
2010 – 2019
- 2019
- [c8]Shawn Tan, Jo-Anne LeFevre:
What strategies do adults use to solve fraction arithmetic problems? CogSci 2019: 3369 - [c7]Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville:
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. ICLR 2019 - [c6]Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville:
Ordered Memory. NeurIPS 2019: 5038-5049 - [i7]Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville:
Investigating Biases in Textual Entailment Datasets. CoRR abs/1906.09635 (2019) - [i6]Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron C. Courville, Yoshua Bengio, Joseph Paul Cohen:
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery. CoRR abs/1910.09570 (2019) - [i5]Yikang Shen, Shawn Tan, Seyedarian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville:
Ordered Memory. CoRR abs/1910.13466 (2019) - 2018
- [c5]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS 2018: 9724-9734 - [i4]Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville:
Generating Contradictory, Neutral, and Entailing Sentences. CoRR abs/1803.02710 (2018) - [i3]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR abs/1809.01818 (2018) - [i2]Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron C. Courville:
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks. CoRR abs/1810.09536 (2018) - 2017
- [i1]Yikang Shen, Shawn Tan, Christopher Joseph Pal, Aaron C. Courville:
Self-organized Hierarchical Softmax. CoRR abs/1707.08588 (2017) - 2016
- [c4]Shawn Tan, Kasia Muldner, Jo-Anne LeFevre:
Solution of division by access to multiplication: Evidence from eye tracking. CogSci 2016 - [c3]Shawn Tan, Khe Chai Sim:
Towards implicit complexity control using variable-depth deep neural networks for automatic speech recognition. ICASSP 2016: 5965-5969 - [c2]Shawn Tan, Khe Chai Sim:
Learning utterance-level normalisation using Variational Autoencoders for robust automatic speech recognition. SLT 2016: 43-49 - 2015
- [c1]Shawn Tan, Khe Chai Sim, Mark J. F. Gales:
Improving the interpretability of deep neural networks with stimulated learning. ASRU 2015: 617-623
Coauthor Index
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