| DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network JL Katzman, U Shaham, A Cloninger, J Bates, T Jiang, Y Kluger BMC medical research methodology 18, 1-12, 2018 | 1734 | 2018 |
| Understanding adversarial training: Increasing local stability of supervised models through robust optimization U Shaham, Y Yamada, S Negahban Neurocomputing 307, 195-204, 2018 | 556 | 2018 |
| Spectralnet: Spectral clustering using deep neural networks U Shaham, K Stanton, H Li, B Nadler, R Basri, Y Kluger International Conference on Learning Representations 2018, 2018 | 367 | 2018 |
| Provable approximation properties for deep neural networks U Shaham, A Cloninger, RR Coifman Applied and Computational Harmonic Analysis 44 (3), 537-557, 2018 | 258 | 2018 |
| Removal of batch effects using distribution-matching residual networks U Shaham, KP Stanton, J Zhao, H Li, K Raddassi, R Montgomery, ... Bioinformatics 33 (16), 2539-2546, 2017 | 181 | 2017 |
| Gating mass cytometry data by deep learning H Li, U Shaham, KP Stanton, Y Yao, RR Montgomery, Y Kluger Bioinformatics 33 (21), 3423-3430, 2017 | 100 | 2017 |
| Defending against adversarial images using basis functions transformations U Shaham, J Garritano, Y Yamada, E Weinberger, A Cloninger, X Cheng, ... arXiv preprint arXiv:1803.10840, 2018 | 76 | 2018 |
| Diffusion nets G Mishne, U Shaham, A Cloninger, I Cohen Applied and Computational Harmonic Analysis 47 (2), 259-285, 2019 | 65 | 2019 |
| Learning by coincidence: Siamese networks and common variable learning U Shaham, RR Lederman Pattern Recognition 74, 52-63, 2018 | 54 | 2018 |
| A deep learning approach to unsupervised ensemble learning U Shaham, X Cheng, O Dror, A Jaffe, B Nadler, J Chang, Y Kluger International conference on machine learning, 30-39, 2016 | 48 | 2016 |
| Differentiable unsupervised feature selection based on a gated laplacian O Lindenbaum, U Shaham, E Peterfreund, J Svirsky, N Casey, Y Kluger Advances in neural information processing systems 34, 1530-1542, 2021 | 43* | 2021 |
| Automated characterization of stenosis in invasive coronary angiography images with convolutional neural networks B Au, U Shaham, S Dhruva, G Bouras, E Cristea, AL MD, A Coppi, ... arXiv preprint arXiv:1807.10597, 2018 | 30 | 2018 |
| Deep unsupervised feature selection by discarding nuisance and correlated features U Shaham, O Lindenbaum, J Svirsky, Y Kluger Neural Networks 152, 34-43, 2022 | 23 | 2022 |
| Stochastic neighbor embedding separates well-separated clusters U Shaham, S Steinerberger arXiv preprint arXiv:1702.02670, 2017 | 20 | 2017 |
| Batch effect removal via batch-free encoding U Shaham BioRxiv, 380816, 2018 | 11 | 2018 |
| Deep neural network to predict local failure following stereotactic body radiation therapy: integrating imaging and clinical data to predict outcomes S Aneja, U Shaham, RJ Kumar, N Pirakitikulr, SK Nath, JB Yu, DJ Carlson, ... International Journal of Radiation Oncology, Biology, Physics 99 (2), S47, 2017 | 8 | 2017 |
| Deep ordinal regression using optimal transport loss and unimodal output probabilities U Shaham, I Zaidman, J Svirsky arXiv preprint arXiv:2011.07607, 2020 | 6 | 2020 |
| Discovery of Single Independent Latent Variable U Shaham, J Svirsky, O Katz, R Talmon Advances in Neural Information Processing Systems, 2022 | 4* | 2022 |
| Learning to Ask Medical Questions using Reinforcement Learning U Shaham, T Zahavy, C Caraballo, S Mahajan, D Massey, H Krumholz Machine Learning for Healthcare Conference, 2-26, 2020 | 3 | 2020 |
| Methods for detecting co-mutated pathways in cancer samples to inform treatment selection T Jiang, U Shaham, F Parisi, R Halaban, A Safonov, H Kluger, ... bioRxiv, 082552, 2016 | 2 | 2016 |
Yuval KlugerYale UniversityVerified email at yale.edu
