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Yichuan Tang
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2020 – today
- 2023
- [j3]Ashiqur Rahaman
, Yichuan Tang
Needle Aligned Ultrasound Image-Guided Access Through Dual-Segment Array. IEEE Trans. Biomed. Eng. 70(9): 2645-2654 (2023) - 2022
- [c14]Yichuan Tang, Isaac Abouaf, Aditya Malik, Araceli B. Gonzalez, Arnav Mishra, Ryosuke Tsumura, Jakub T. Kaminski, Igor Sorokin, Haichong K. Zhang:
Mirror-integrated ultrasound image-guided access. Medical Imaging: Image-Guided Procedures 2022 - 2020
- [i8]Yichuan Charlie Tang:
Towards Learning Multi-agent Negotiations via Self-Play. CoRR abs/2001.10208 (2020)
2010 – 2019
- 2019
- [c13]Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov:
Worst Cases Policy Gradients. CoRL 2019: 1078-1093 - [c12]Yichuan Tang:
Towards Learning Multi-Agent Negotiations via Self-Play. ICCV Workshops 2019: 2427-2435 - [c11]Yichuan Charlie Tang, Ruslan Salakhutdinov:
Multiple Futures Prediction. NeurIPS 2019: 15398-15408 - [i7]Yichuan Charlie Tang, Ruslan Salakhutdinov:
Multiple Futures Prediction. CoRR abs/1911.00997 (2019) - [i6]Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov:
Worst Cases Policy Gradients. CoRR abs/1911.03618 (2019) - [i5]Lionel Blondé, Yichuan Charlie Tang, Jian Zhang, Russ Webb:
Relational Mimic for Visual Adversarial Imitation Learning. CoRR abs/1912.08444 (2019) - 2016
- [b1]Yichuan Tang:
Learning Generative Models Using Structured Latent Variables. University of Toronto, Canada, 2016 - [c10]Margot Lisa-Jing Yann, Yichuan Tang:
Learning Deep Convolutional Neural Networks for X-Ray Protein Crystallization Image Analysis. AAAI 2016: 1373-1379 - 2015
- [j2]Ian J. Goodfellow
Challenges in representation learning: A report on three machine learning contests. Neural Networks 64: 59-63 (2015) - 2014
- [c9]Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov:
Learning Generative Models with Visual Attention. NIPS 2014: 1808-1816 - 2013
- [c8]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Tensor Analyzers. ICML (3) 2013: 163-171 - [c7]Ian J. Goodfellow
Challenges in Representation Learning: A Report on Three Machine Learning Contests. ICONIP (3) 2013: 117-124 - [c6]Yichuan Tang, Ruslan Salakhutdinov:
Learning Stochastic Feedforward Neural Networks. NIPS 2013: 530-538 - [i4]Yichuan Tang:
Deep Learning using Support Vector Machines. CoRR abs/1306.0239 (2013) - [i3]Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-Hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio:
Challenges in Representation Learning: A report on three machine learning contests. CoRR abs/1307.0414 (2013) - [i2]Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov:
Learning generative models with visual attention. CoRR abs/1312.6110 (2013) - 2012
- [c5]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Robust Boltzmann Machines for recognition and denoising. CVPR 2012: 2264-2271 - [c4]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Mixtures of Factor Analysers. ICML 2012 - [c3]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Lambertian Networks. ICML 2012 - [c2]Yichuan Tang, Abdel-rahman Mohamed:
Multiresolution Deep Belief Networks. AISTATS 2012: 1203-1211 - [i1]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Mixtures of Factor Analysers. CoRR abs/1206.4635 (2012) - 2011
- [j1]Terrence C. Stewart, Yichuan Tang, Chris Eliasmith:
A biologically realistic cleanup memory: Autoassociation in spiking neurons. Cogn. Syst. Res. 12(2): 84-92 (2011) - 2010
- [c1]Yichuan Tang, Chris Eliasmith:
Deep networks for robust visual recognition. ICML 2010: 1055-1062
Coauthor Index
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