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Rahul G. Krishnan
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Cited by
Year
Variational autoencoders for collaborative filtering
D Liang, RG Krishnan, MD Hoffman, T Jebara
Proceedings of the 2018 World Wide Web Conference, 689-698, 2018
15182018
Structured Inference Networks for Nonlinear State Space Models
RG Krishnan, U Shalit, D Sontag
arXiv preprint arXiv:1609.09869, 2016
5732016
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
5262022
Deep Kalman Filters
RG Krishnan, U Shalit, D Sontag
arXiv preprint arXiv:1511.05121, 2015
4592015
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
CoRR, 2023
111*2023
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
1002018
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
RJ Chen, RG Krishnan
arXiv preprint arXiv:2203.00585, 2022
832022
Barrier Frank-Wolfe for marginal inference
RG Krishnan, S Lacoste-Julien, D Sontag
Advances in Neural Information Processing Systems, 532-540, 2015
502015
Representation learning approaches to detect false arrhythmia alarms from ecg dynamics
EP Lehman, RG Krishnan, X Zhao, RG Mark, LH Lehman
Machine learning for healthcare conference, 571-586, 2018
352018
Machine learning in computational histopathology: Challenges and opportunities
M Cooper, Z Ji, RG Krishnan
Genes, Chromosomes and Cancer 62 (9), 540-556, 2023
282023
Performance of Large Language Models on Medical Oncology Examination Questions
JB Longwell, I Hirsch, F Binder, GAG Conchas, D Mau, R Jang, ...
JAMA Network Open 7 (6), e2417641-e2417641, 2024
212024
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
212013
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
202022
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
19*2022
Neural pharmacodynamic state space modeling
ZM Hussain, RG Krishnan, D Sontag
International Conference on Machine Learning, 4500-4510, 2021
152021
A Learning Based Hypothesis Test for Harmful Covariate Shift
T Ginsberg, Z Liang, RG Krishnan
arXiv preprint arXiv:2212.02742, 2022
142022
Duett: Dual event time transformer for electronic health records
A Labach, A Pokhrel, XS Huang, S Zuberi, SE Yi, M Volkovs, T Poutanen, ...
Machine Learning for Healthcare Conference, 403-422, 2023
112023
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
102022
End-to-end causal effect estimation from unstructured natural language data
N Dhawan, L Cotta, K Ullrich, RG Krishnan, CJ Maddison
Advances in Neural Information Processing Systems 37, 77165-77199, 2025
92025
A Geometric Explanation of the Likelihood OOD Detection Paradox
H Kamkari, BL Ross, JC Cresswell, AL Caterini, RG Krishnan, ...
arXiv preprint arXiv:2403.18910, 2024
92024
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