Rahul G. Krishnan 个人学术档案

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引用	2983	2744
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David SontagProfessor, Massachusetts Institute of Technology在 csail.mit.edu 的电子邮件经过验证
Matthew D. HoffmanResearch Scientist, Google Research在 google.com 的电子邮件经过验证
Dawen LiangResearch Scientist, Netflix Inc.在 netflix.com 的电子邮件经过验证
Uri ShalitAssociate Professor, Technion - Israel Institute of Technology在 technion.ac.il 的电子邮件经过验证
Tony JebaraSpotify在 spotify.com 的电子邮件经过验证
Richard J. ChenBrigham and Women's Hospital, Harvard Medical School在 g.harvard.edu 的电子邮件经过验证
Faisal MahmoodAssociate Professor, Harvard University在 fas.harvard.edu 的电子邮件经过验证
Michael CooperPhD Student, University of Toronto在 cs.toronto.edu 的电子邮件经过验证
Vahid BalazadehPhD in Computer Science - University of Toronto在 cs.toronto.edu 的电子邮件经过验证
Jimmy BaUniversity of Toronto在 cs.toronto.edu 的电子邮件经过验证
Bo WangChief AI Scientist,UHN; CIFAR AI Chair, Vector Institute; Assistant Professor, U of Toronto在 vectorinstitute.ai 的电子邮件经过验证
Vasilis SyrgkanisAssistant Professor, Stanford University在 stanford.edu 的电子邮件经过验证
Pascal N. TyrrellDepartment of Medical Imaging - University of Toronto在 tyrrell4innovation.ca 的电子邮件经过验证
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / Mila在 iro.umontreal.ca 的电子邮件经过验证
Zeshan M HussainMD-PhD Student, Harvard Medical School, MIT在 mit.edu 的电子邮件经过验证
Edward De BrouwerYale University在 esat.kuleuven.be 的电子邮件经过验证
Hamidreza KamkariLayer6 AI, University of Toronto在 layer6.ai 的电子邮件经过验证
Narges RazavianNew York University Medical Center在 nyumc.org 的电子邮件经过验证
Tom GinsbergResearch Scientist and CTO, BEIT Canada Inc.在 beit.tech 的电子邮件经过验证
Ricardo Baptistavon Karman Instructor, California Institute of Technology在 caltech.edu 的电子邮件经过验证

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Rahul G. Krishnan

University of Toronto

在 cs.toronto.edu 的电子邮件经过验证 - 首页

Machine Learning Artificial Intelligence Healthcare Probabilistic models


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Variational autoencoders for collaborative filtering D Liang, RG Krishnan, MD Hoffman, T Jebara Proceedings of the 2018 World Wide Web Conference, 689-698, 2018	1282	2018
Structured Inference Networks for Nonlinear State Space Models RG Krishnan, U Shalit, D Sontag arXiv preprint arXiv:1609.09869, 2016	522	2016
Deep Kalman Filters RG Krishnan, U Shalit, D Sontag arXiv preprint arXiv:1511.05121, 2015	424	2015
Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning RJ Chen, C Chen, Y Li, TY Chen, AD Trister, RG Krishnan, F Mahmood Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	315	2022
On the challenges of learning with inference networks on sparse, high-dimensional data RG Krishnan, D Liang, MD Hoffman The 21st International Conference on Artificial Intelligence and Statistics, 2018	91	2018
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology RJ Chen, RG Krishnan arXiv preprint arXiv:2203.00585, 2022	68	2022
Clinical camel: An open-source expert-level medical language model with dialogue-based knowledge encoding A Toma, PR Lawler, J Ba, RG Krishnan, BB Rubin, B Wang arXiv preprint arXiv:2305.12031 1, 2023	54	2023
Barrier Frank-Wolfe for marginal inference RG Krishnan, S Lacoste-Julien, D Sontag Advances in Neural Information Processing Systems, 532-540, 2015	48	2015
Representation Learning Approaches to Detect False Arrhythmia Alarms from ECG Dynamics EP Lehman, RG Krishnan, X Zhao, RG Mark, HL Li-wei Machine Learning for Healthcare Conference, 571-586, 2018	31	2018
Early detection of diabetes from health claims R Krishnan, N Razavian, Y Choi, S Nigam, S Blecker, A Schmidt, ... Machine Learning in Healthcare Workshop, NIPS, 1-5, 2013	21	2013
Partial identification of treatment effects with implicit generative models V Balazadeh Meresht, V Syrgkanis, RG Krishnan Advances in Neural Information Processing Systems 35, 22816-22829, 2022	17*	2022
Neural pharmacodynamic state space modeling ZM Hussain, RG Krishnan, D Sontag International Conference on Machine Learning, 4500-4510, 2021	14	2021
Machine learning in computational histopathology: Challenges and opportunities M Cooper, Z Ji, RG Krishnan Genes, Chromosomes and Cancer 62 (9), 540-556, 2023	12	2023
A Learning Based Hypothesis Test for Harmful Covariate Shift T Ginsberg, Z Liang, RG Krishnan arXiv preprint arXiv:2212.02742, 2022	12	2022
Clustering Interval-Censored Time-Series for Disease Phenotyping IY Chen, RG Krishnan, D Sontag Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6211-6221, 2022	9	2022
Hierarchical Optimal Transport for Comparing Histopathology Datasets A Yeaton, RG Krishnan, R Mieloszyk, D Alvarez-Melis, G Huynh arXiv preprint arXiv:2204.08324, 2022	8	2022
Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet? A Hibi, M Jaberipour, MD Cusimano, A Bilbily, RG Krishnan, RI Aviv, ... Medicine 101 (47), e31848, 2022	7	2022
Clinical camel: An open expert-level medical language model with dialogue-based knowledge encoding A Toma, PR Lawler, J Ba, RG Krishnan, BB Rubin, B Wang arXiv preprint arXiv:2305.12031, 2023	5	2023
HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding W Ren, R Zeng, T Wu, T Zhu, RG Krishnan Machine Learning for Healthcare Conference, 198-223, 2022	5	2022
Learning predictive checklists from continuous medical data Y Makhija, E De Brouwer, RG Krishnan arXiv preprint arXiv:2211.07076, 2022	5	2022

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