Rahul G. Krishnan

82 papers A* 16A 4Journal 52Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Can we generate portable representations for clinical time series data using LLMs? CoRR Zongliang Ji, Yifei Sun, André Amaral, Anna Goldenberg, Rahul G. Krishnan
2026	J	`jnl`	Dialogue to Question Generation for Evidence-based Medical Guideline Agent Development. CoRR Zongliang Ji, Ziyang Zhang, Xincheng Tan, Matthew Thompson, Anna Goldenberg, Carl Yang, Rahul G. Krishnan, Fan Zhang
2026	J	`jnl`	Frequentist Consistency of Prior-Data Fitted Networks for Causal Inference. CoRR Valentyn Melnychuk, Vahid Balazadeh, Stefan Feuerriegel, Rahul G. Krishnan
2026	J	`jnl`	MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models. CoRR Chen-Hao Chao, Wei-Fang Sun, Junwei Quan, Chun-Yi Lee, Rahul G. Krishnan
2025	J	`jnl`	A generalizable 3D framework and model for self-supervised learning in medical imaging. CoRR Tony Xu, Sepehr Hosseini, Chris Anderson, Anthony Rinaldi, Rahul G. Krishnan, Anne L. Martel, Maged Goubran
2025	J	`jnl`	A generalizable 3D framework and model for self-supervised learning in medical imaging. npj Digit. Medicine Tony Xu, Sepehr Hosseini, Chris Anderson, Anthony Rinaldi, Rahul G. Krishnan, Anne L. Martel, Maged Goubran
2025	J	`jnl`	Adaptive Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge. CoRR Mohammad R. Rezaei, Reza Saadati Fard, Jayson Parker, Rahul G. Krishnan, Milad Lankarany
2025	—	`conf`	Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge. EMNLP (Findings) Mohammad R. Rezaei, Reza Saadati Fard, Jayson Parker, Rahul G. Krishnan, Milad Lankarany
2025	A*	`conf`	AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling. ICML Alexander Capstick, Rahul G. Krishnan, Payam M. Barnaghi
2025	J	`jnl`	Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking. CoRR Chen-Hao Chao, Wei-Fang Sun, Hanwen Liang, Chun-Yi Lee, Rahul G. Krishnan
2025	J	`jnl`	CausalPFN: Amortized Causal Effect Estimation via In-Context Learning. CoRR Vahid Balazadeh Meresht, Hamidreza Kamkari, Valentin Thomas, Benson Li, Junwei Ma, Jesse C. Cresswell, Rahul G. Krishnan
2025	A*	`conf`	Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift. ICML Minh Nguyen Nhat To, Paul F. R. Wilson, Viet Nguyen, Mohamed Harmanani, Michael Cooper, Fahimeh Fooladgar, Purang Abolmaesumi, Parvin Mousavi, Rahul G. Krishnan
2025	J	`jnl`	Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift. CoRR Minh Nguyen Nhat To, Paul F. R. Wilson, Viet Nguyen, Mohamed Harmanani, Michael Cooper, Fahimeh Fooladgar, Purang Abolmaesumi, Parvin Mousavi, Rahul G. Krishnan
2025	J	`jnl`	DynaSubVAE: Adaptive Subgrouping for Scalable and Robust OOD Detection. CoRR Tina Behrouzi, Sana Tonekaboni, Rahul G. Krishnan, Anna Goldenberg
2025	—	`conf`	ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders. CHIL Zongliang Ji, Andre Carlos Kajdacsy-Balla Amaral, Anna Goldenberg, Rahul G. Krishnan
2025	J	`jnl`	ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders. CoRR Zongliang Ji, Andre Carlos Kajdacsy-Balla Amaral, Anna Goldenberg, Rahul G. Krishnan
2025	J	`jnl`	Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium. CoRR Amin Adibi, Xu Cao, Zongliang Ji, Jivat Neet Kaur, Winston Chen, Elizabeth Healey, Brighton Nuwagira, Wenqian Ye, Geoffrey Woollard, Maxwell A. Xu, Hejie Cui, Johnny Xi, Trenton Chang, Vasiliki Bikia, Nicole Zhang, Ayush Noori, Yuan Xia, Md. Belal Hossain, Hanna A. Frank, Alina Peluso, Yuan Pu, Shannon Zejiang Shen, John Wu, Adibvafa Fallahpour, Sazan Mahbub, Ross Duncan, Yuwei Zhang, Yurui Cao, Zuheng Xu, Michael Craig, Rahul G. Krishnan, Rahmatollah Beheshti, James M. Rehg, Mohammad Ehsanul Karim, Megan Coffee, Leo Anthony Celi, Jason Alan Fries, Mohsen Sadatsafavi, Dennis L. Shung, Shannon K. McWeeney, Jessica Dafflon, Sarah Jabbour
2025	J	`jnl`	Red Teaming Large Language Models for Healthcare. CoRR Vahid Balazadeh Meresht, Michael Cooper, David Pellow, Atousa Assadi, Jennifer Bell, Jim Fackler, Gabriel Funingana, Spencer Gable-Cook, Anirudh Gangadhar, Abhishek Jaiswal, Sumanth Kaja, Christopher Khoury, Randy Lin, Kaden McKeen, Sara Naimimohasses, Khashayar Namdar, Aviraj Newatia, Allan Pang, Anshul Pattoo, Sameer Peesapati, Diana Prepelita, Bogdana Rakova, Saba Sadatamin, Rafael Schulman, Ajay Shah, Syed Azhar Shah, Syed Ahmar Shah, Babak Taati, Balagopal Unnikrishnan, Stephanie Williams, Rahul G. Krishnan
2025	J	`jnl`	Reliably detecting model failures in deployment without labels. CoRR Viet Nguyen, Changjian Shui, Vijay Giri, Siddarth Arya, Amol Verma, Fahad Razak, Rahul G. Krishnan
2025	A*	`conf`	Teaching LLMs How to Learn with Contextual Fine-Tuning. ICLR Younwoo Choi, Muhammad Adil Asif, Ziwen Han, John Willes, Rahul G. Krishnan
2025	J	`jnl`	Teaching LLMs How to Learn with Contextual Fine-Tuning. CoRR Younwoo Choi, Muhammad Adil Asif, Ziwen Han, John Willes, Rahul G. Krishnan
2024	A*	`conf`	A Geometric Explanation of the Likelihood OOD Detection Paradox. ICML Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini, Rahul G. Krishnan, Gabriel Loaiza-Ganem
2024	J	`jnl`	A Geometric Explanation of the Likelihood OOD Detection Paradox. CoRR Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini, Rahul G. Krishnan, Gabriel Loaiza-Ganem
2024	A*	`conf`	End-To-End Causal Effect Estimation from Unstructured Natural Language Data. NeurIPS Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison
2024	J	`jnl`	End-To-End Causal Effect Estimation from Unstructured Natural Language Data. CoRR Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison
2024	J	`jnl`	Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling. CoRR Mohammad R. Rezaei, Rahul G. Krishnan, Milos R. Popovic, Milad Lankarany
2024	A*	`conf`	InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation. ICML Jacob Yoke Hong Si, Wendy Yusi Cheng, Michael Cooper, Rahul G. Krishnan
2024	J	`jnl`	InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation. CoRR Jacob Yoke Hong Si, Wendy Yusi Cheng, Michael Cooper, Rahul G. Krishnan
2024	J	`jnl`	Learning Predictive Checklists with Probabilistic Logic Programming. CoRR Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan
2024	J	`jnl`	Measurement Scheduling for ICU Patients with Offline Reinforcement Learning. CoRR Zongliang Ji, Anna Goldenberg, Rahul G. Krishnan
2024	—	`conf`	NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild. MLHC Rishit Dagli, Atsuhiro Hibi, Rahul G. Krishnan, Pascal N. Tyrrell
2024	J	`jnl`	NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild. CoRR Rishit Dagli, Atsuhiro Hibi, Rahul G. Krishnan, Pascal N. Tyrrell
2024	J	`jnl`	Personalized Adaptation via In-Context Preference Learning. CoRR Allison Lau, Younwoo Choi, Vahid Balazadeh Meresht, Keertana Chidambaram, Vasilis Syrgkanis, Rahul G. Krishnan
2024	—	`conf`	Predicting Long-Term Allograft Survival in Liver Transplant Recipients. MLHC Xiang Gao, Michael Cooper, Maryam Naghibzadeh, Amirhossein Azhie, Mamatha Bhat, Rahul G. Krishnan
2024	J	`jnl`	Predicting Long-Term Allograft Survival in Liver Transplant Recipients. CoRR Xiang Gao, Michael Cooper, Maryam Naghibzadeh, Amirhossein Azhie, Mamatha Bhat, Rahul G. Krishnan
2024	A*	`conf`	Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity. NeurIPS Vahid Balazadeh Meresht, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis
2024	J	`jnl`	Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity. CoRR Vahid Balazadeh Meresht, Keertana Chidambaram, Viet Nguyen, Rahul G. Krishnan, Vasilis Syrgkanis
2024	J	`jnl`	Synthetic Vision: Training Vision-Language Models to Understand Physics. CoRR Vahid Balazadeh Meresht, Mohammadmehdi Ataei, Hyunmin Cheong, Amir Hosein Khasahmadi, Rahul G. Krishnan
2024	J	`jnl`	Using Large Language Models for Expert Prior Elicitation in Predictive Modelling. CoRR Alexander Capstick, Rahul G. Krishnan, Payam M. Barnaghi
2023	A*	`conf`	A Learning Based Hypothesis Test for Harmful Covariate Shift. ICLR Tom Ginsberg, Zhongyuan Liang, Rahul G. Krishnan
2023	A*	`conf`	Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections. ICLR Edward De Brouwer, Rahul G. Krishnan
2023	J	`jnl`	Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections. CoRR Edward De Brouwer, Rahul G. Krishnan
2023	J	`jnl`	Automated screening of computed tomography using weakly supervised anomaly detection. Int. J. Comput. Assist. Radiol. Surg. Atsuhiro Hibi, Michael D. Cusimano, Alexander Bilbily, Rahul G. Krishnan, Pascal N. Tyrrell
2023	—	`conf`	Characterizing the Progression of Pulmonary Edema Severity: Can Pairwise Comparisons in Radiology Reports Help? CinC Stephanie M. Hu, Steven Horng, Seth J. Berkowitz, Ruizhi Liao, Rahul G. Krishnan, Li-Wei H. Lehman, Roger G. Mark
2023	J	`jnl`	Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding. CoRR Augustin Toma, Patrick R. Lawler, Jimmy Ba, Rahul G. Krishnan, Barry B. Rubin, Bo Wang
2023	J	`jnl`	Copula-Based Deep Survival Models for Dependent Censoring. CoRR Ali Hossein Gharari Foomani, Michael Cooper, Russell Greiner, Rahul G. Krishnan
2023	A	`conf`	Copula-based deep survival models for dependent censoring. UAI Ali Hossein Gharari Foomani, Michael Cooper, Russell Greiner, Rahul G. Krishnan
2023	—	`conf`	DuETT: Dual Event Time Transformer for Electronic Health Records. MLHC Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan
2023	J	`jnl`	DuETT: Dual Event Time Transformer for Electronic Health Records. CoRR Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan
2023	J	`jnl`	MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting. CoRR Linfeng Du, Ji Xin, Alex Labach, Saba Zuberi, Maksims Volkovs, Rahul G. Krishnan
2023	J	`jnl`	OCDaf: Ordered Causal Discovery with Autoregressive Flows. CoRR Hamidreza Kamkari, Vahid Zehtab, Vahid Balazadeh Meresht, Rahul G. Krishnan
2023	A*	`conf`	Structured Neural Networks for Density Estimation and Causal Inference. NeurIPS Asic Q. Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, Rahul G. Krishnan
2023	J	`jnl`	Structured Neural Networks for Density Estimation and Causal Inference. CoRR Asic Q. Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, Rahul G. Krishnan
2022	J	`jnl`	A Learning Based Hypothesis Test for Harmful Covariate Shift. CoRR Tom Ginsberg, Zhongyuan Liang, Rahul G. Krishnan
2022	A*	`conf`	Clustering Interval-Censored Time-Series for Disease Phenotyping. AAAI Irene Y. Chen, Rahul G. Krishnan, David A. Sontag
2022	—	`conf`	HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding. MLHC Weiming Ren, Ruijing Zeng, Tongzi Wu, Tianshu Zhu, Rahul G. Krishnan
2022	J	`jnl`	HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding. CoRR Weiming Ren, Ruijing Zeng, Tongzi Wu, Tianshu Zhu, Rahul G. Krishnan
2022	—	`conf`	Hierarchical Optimal Transport for Comparing Histopathology Datasets. MIDL Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh
2022	J	`jnl`	Hierarchical Optimal Transport for Comparing Histopathology Datasets. CoRR Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh
2022	J	`jnl`	Learning predictive checklists from continuous medical data. CoRR Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan
2022	J	`jnl`	Mixture-of-experts VAEs can disregard variation in surjective multimodal data. CoRR Jannik Wolff, Tassilo Klein, Moin Nabi, Rahul G. Krishnan, Shinichi Nakajima
2022	A*	`conf`	Partial Identification of Treatment Effects with Implicit Generative Models. NeurIPS Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G. Krishnan
2022	J	`jnl`	Partial Identification of Treatment Effects with Implicit Generative Models. CoRR Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G. Krishnan
2022	A*	`conf`	Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning. CVPR Richard J. Chen, Chengkuan Chen, Yicong Li, Tiffany Y. Chen, Andrew D. Trister, Rahul G. Krishnan, Faisal Mahmood
2022	J	`jnl`	Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning. CoRR Richard J. Chen, Chengkuan Chen, Yicong Li, Tiffany Y. Chen, Andrew D. Trister, Rahul G. Krishnan, Faisal Mahmood
2022	J	`jnl`	Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology. CoRR Richard J. Chen, Rahul G. Krishnan
2022	A	`conf`	Using time-series privileged information for provably efficient learning of prediction models. AISTATS Rickard K. A. Karlsson, Martin Willbo, Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag, Fredrik Johansson
2021	J	`jnl`	Clustering Left-Censored Multivariate Time-Series. CoRR Irene Y. Chen, Rahul G. Krishnan, David A. Sontag
2021	A*	`conf`	Neural Pharmacodynamic State Space Modeling. ICML Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag
2021	J	`jnl`	Neural Pharmacodynamic State Space Modeling. CoRR Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag
2021	J	`jnl`	Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models. CoRR Rickard Karlsson, Martin Willbo, Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag, Fredrik D. Johansson
2018	A	`conf`	Max-margin learning with the Bayes factor. UAI Rahul G. Krishnan, Arjun Khandelwal, Rajesh Ranganath, David A. Sontag
2018	A	`conf`	On the challenges of learning with inference networks on sparse, high-dimensional data. AISTATS Rahul G. Krishnan, Dawen Liang, Matthew D. Hoffman
2018	—	`conf`	Representation Learning Approaches to Detect False Arrhythmia Alarms from ECG Dynamics. MLHC Eric P. Lehman, Rahul G. Krishnan, Xiaopeng Zhao, Roger G. Mark, Li-Wei H. Lehman
2018	A*	`conf`	Variational Autoencoders for Collaborative Filtering. WWW Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2018	J	`jnl`	Variational Autoencoders for Collaborative Filtering. CoRR Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2017	J	`jnl`	On the challenges of learning with inference networks on sparse, high-dimensional data. CoRR Rahul G. Krishnan, Dawen Liang, Matthew D. Hoffman
2017	A*	`conf`	Structured Inference Networks for Nonlinear State Space Models. AAAI Rahul G. Krishnan, Uri Shalit, David A. Sontag
2016	J	`jnl`	Structured Inference Networks for Nonlinear State Space Models. CoRR Rahul G. Krishnan, Uri Shalit, David A. Sontag
2015	—	`conf`	Barrier Frank-Wolfe for Marginal Inference. NIPS Rahul G. Krishnan, Simon Lacoste-Julien, David A. Sontag
2015	J	`jnl`	Barrier Frank-Wolfe for Marginal Inference. CoRR Rahul G. Krishnan, Simon Lacoste-Julien, David A. Sontag
2015	J	`jnl`	Deep Kalman Filters. CoRR Rahul G. Krishnan, Uri Shalit, David A. Sontag