Beilun Wang
Beilun Wang
PhD student of Computer Science, University of Virginia
Verified email at virginia.edu
Title
Cited by
Cited by
Year
Deep motif dashboard: Visualizing and understanding genomic sequences using deep neural networks
J Lanchantin, R Singh, B Wang, Y Qi
Pacific Symposium on Biocomputing 2017, 254-265, 2017
932017
Deepcloak: Masking deep neural network models for robustness against adversarial samples
J Gao, B Wang, Z Lin, W Xu, Y Qi
arXiv preprint arXiv:1702.06763, 2017
582017
A theoretical framework for robustness of (deep) classifiers under adversarial noise
B Wang, J Gao, Y Qi
arXiv preprint arXiv:1612.00334, 2016
362016
A theoretical framework for robustness of (deep) classifiers against adversarial examples
B Wang, J Gao, Y Qi
arXiv preprint arXiv:1612.00334, 2016
28*2016
Deepmask: Masking dnn models for robustness against adversarial samples
J Gao, B Wang, Y Qi
arXiv preprint arXiv:1702.06763 22, 2017
92017
GaKCo: A Fast Gapped k-mer String Kernel Using Counting
R Singh, A Sekhon, K Kowsari, J Lanchantin, B Wang, Y Qi
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
82017
A constrained ℓ 1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models
B Wang, R Singh, Y Qi
Machine Learning 106 (9), 1381-1417, 2017
72017
Pacific Symposium on Biocomputing 2017
J Lanchantin, R Singh, B Wang, Y Qi
World Scientific,, 2017
52017
Kernelized information-theoretic metric learning for cancer diagnosis using high-dimensional molecular profiling data
F Xiong, M Kam, L Hrebien, B Wang, Y Qi
ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (4), 1-23, 2016
52016
Deep gdashboard: Visualizing and understanding genomic sequences using deep neural networks
J Lanchantin, R Singh, B Wang, Y Qi
52016
Fast and scalable learning of sparse changes in high-dimensional gaussian graphical model structure
B Wang, Y Qi
International Conference on Artificial Intelligence and Statistics, 1691-1700, 2018
42018
A constrained, weighted-l1 minimization approach for joint discovery of heterogeneous neural connectivity graphs
C Singh, B Wang, Y Qi
arXiv preprint arXiv:1709.04090, 2017
42017
A fast and scalable joint estimator for learning multiple related sparse gaussian graphical models
B Wang, J Gao, Y Qi
Artificial Intelligence and Statistics, 1168-1177, 2017
22017
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models
B Wang, A Sekhon, Y Qi
International Conference on Machine Learning, 5161-5170, 2018
12018
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables
J Zhang, M Wang, Q Li, S Wang, X Chang, B Wang
1
How Decisions Are Made in Brains: Unpack “Black Box” of CNN With Ms. Pac-Man Video Game
B Wang, R Ma, J Kuang, Y Zhang
IEEE Access 8, 142446-142458, 2020
2020
Differential Network Learning Beyond Data Samples
A Sekhon, B Wang, Z Wang, Y Qi
arXiv preprint arXiv:2004.11494, 2020
2020
Fast and Scalable Estimator for Sparse and Unit-Rank Higher-Order Regression Models
J Zhang, B Wang
arXiv preprint arXiv:1912.01450, 2019
2019
Sparse and Low-Rank Tensor Regression via Parallel Proximal Method
J Zhang, B Wang
arXiv preprint arXiv:1911.12965, 2019
2019
Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models
A Sekhon, B Wang, Y Qi
bioRxiv, 716852, 2019
2019
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