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Li Yao
Li Yao
PhD, Lead Data Scientist at Enlitic Inc.
Verified email at enlitic.com - Homepage
Title
Cited by
Cited by
Year
Describing videos by exploiting temporal structure
L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville
Proceedings of the IEEE international conference on computer vision, 4507-4515, 2015
13522015
Delving deeper into convolutional networks for learning video representations
N Ballas, L Yao, C Pal, A Courville
arXiv preprint arXiv:1511.06432, 2015
8872015
Generalized denoising auto-encoders as generative models
Y Bengio, L Yao, G Alain, P Vincent
Neural Information Processing Systems (NIPS) 2013, 2013
7542013
Learning to diagnose from scratch by exploiting dependencies among labels
L Yao, E Poblenz, D Dagunts, B Covington, D Bernard, K Lyman
arXiv preprint arXiv:1710.10501, 2017
4402017
Weakly supervised medical diagnosis and localization from multiple resolutions
L Yao, J Prosky, E Poblenz, B Covington, K Lyman
arXiv preprint arXiv:1803.07703, 2018
1562018
GSNs: generative stochastic networks
G Alain, Y Bengio, L Yao, J Yosinski, E Thibodeau-Laufer, S Zhang, ...
Information and Inference: A Journal of the IMA 5 (2), 210-249, 2016
782016
Video description generation incorporating spatio-temporal features and a soft-attention mechanism
L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville
arXiv preprint arXiv:1502.08029 6 (2), 201-211, 2015
632015
Iterative Neural Autoregressive Distribution Estimator (NADE-k)
T Raiko, L Yao, K Cho, Y Bengio
Neural Information Processing Systems (NIPS) 2014, 2014
552014
A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging
KL Li Yao, Jordan Prosky, Ben Covington
Medical Imaging with Deep Learning (MIDL), 2019
42*2019
Bounding the test log-likelihood of generative models
Y Bengio, L Yao, K Cho
International Conference on Learning Representations (ICLR) 2013, arXiv …, 2013
262013
On the Equivalence Between Deep NADE and Generative Stochastic Networks
L Yao, S Ozair, K Cho, Y Bengio
ECML/PKDD 2014, European Conference on Machine Learning and Principles and …, 2014
152014
Multimodal Transitions for Generative Stochastic Networks
S Ozair, L Yao, Y Bengio
NIPS13 Deep learning workshop, arXiv preprint arXiv:1312.5578, 2013
102013
Trainable performance upper bounds for image and video captioning
L Yao, N Ballas, K Cho, JR Smith, Y Bengio, L Yao, N Ballas, K Cho, ...
arXiv preprint arXiv 1511, 2015
62015
Empirical performance upper bounds for image and video captioning
L Yao, N Ballas, K Cho, JR Smith, Y Bengio
22016
Stacked calibration of off-policy policy evaluation for video game matchmaking
E Laufer, RC Ferrari, L Yao, O Delalleau, Y Bengio
2013 IEEE Conference on Computational Inteligence in Games (CIG), 1-8, 2013
12013
Anomaly detection and location with an application to an energy management system
L Yao
Aalto University, 2010
12010
Caveats in Generating Medical Imaging Labels from Radiology Reports
AU Tobi Olatunji, Li Yao, Ben Covington, Alexander Rhodes
Medical Imaging with Deep Learning (MIDL), 2019
2019
Efficient and Accurate Abnormality Mining from Radiology Reports with Customized False Positive Reduction
KL Nithya Attaluri, Ahmed Nasir, Carolynne Powe, Harold Racz, Ben Covington ...
https://arxiv.org/abs/1810.00967, 2018
2018
Locating Anomalies Using Bayesian Factorizations and Masks.
L Yao, A Lendasse, F Corona
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2011
2011
An Online Evaluation Platform for Proactive Information Retrieval Task
L Yao, A Ajanki
Pahikkala, Väyrynen, Kortela and Airola (eds.), 79, 2010
2010
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Articles 1–20