Rajesh Ranganath

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 22 papers. Top paper: “A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients”.

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

npj Digital Medicine(2020)10.1038/s41746-020-00343-x

N/A

0DataRank · unranked

68 citations

Vincent J. Major, Mukund Sudarshan, Jesse Burk‐Rafel, Peter Stella, Hardev Randhawa +19 more

Reproducibility in machine learning for health research: Still a ways to go

Science Translational Medicine(2021)10.1126/scitranslmed.abb1655

N/A

0DataRank · unranked

266 citations

Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Luca Foschini, Marzyeh Ghassemi +1 more

Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations

arXiv (Cornell University)(2021)10.48550/arxiv.2107.00520

N/A

0DataRank · unranked

5 citations

Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath, Aahlad Puli

Survival Mixture Density Networks

PubMed(2022)10.48550/arxiv.2208.10759

N/A

0DataRank · unranked

1 citations

Goldstein, Mark, Rajesh Ranganath, Xintian Han

Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets

arXiv (Cornell University)(2022)10.48550/arxiv.2206.11925

N/A

0DataRank · unranked

4 citations

Veronica Tozzo, John M. Higgins, Rajesh Ranganath, Lily H. Zhang

Holdout predictive checks for Bayesian model criticism

Journal of the Royal Statistical Society Series B (Statistical Methodology)(2023)10.1093/jrsssb/qkad105

N/A

0DataRank · unranked

11 citations

David M. Blei, Rajesh Ranganath, Gemma E. Moran

Conditional average treatment effect estimation with marginally constrained models

Journal of Causal Inference(2023)10.1515/jci-2022-0027

N/A

0DataRank · unranked

5 citations

Rajesh Ranganath, Wouter A. C. van Amsterdam

An Effective Meaningful Way to Evaluate Survival Models

arXiv (Cornell University)(2023)10.48550/arxiv.2306.01196

N/A

0DataRank · unranked

4 citations

Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath +3 more

Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection

Proceedings of the AAAI Conference on Artificial Intelligence(2023)10.1609/aaai.v37i12.26785

N/A

0DataRank · unranked

4 citations

Rajesh Ranganath, Lily H. Zhang

When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations

arXiv (Cornell University)(2023)10.48550/arxiv.2308.04431

N/A

0DataRank · unranked

4 citations

Lily Zhang, Aahlad Puli, Rajesh Ranganath, Rhys Compton

A dynamic risk score for early prediction of cardiogenic shock using machine learning

arXiv (Cornell University)(2023)10.48550/arxiv.2303.12888

N/A

0DataRank · unranked

1 citations

Albert Lui, Goldstein, Mark, Mukund Sudarshan, Andrea Tinsay, Cindy Tsui +16 more

Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection

arXiv (Cornell University)(2023)10.48550/arxiv.2302.04132

N/A

0DataRank · unranked

0 citations

Rajesh Ranganath, Lily H. Zhang

Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions

arXiv (Cornell University)(2023)10.48550/arxiv.2302.07261

N/A

0DataRank · unranked

0 citations

Goldstein, Mark, Rajesh Ranganath, Raghav Singhal

Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation

PubMed(2023)10.48550/arxiv.2302.12893

N/A

0DataRank · unranked

0 citations

Adriel Saporta, Rajesh Ranganath, Neil Jethani

Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning

European Heart Journal Acute Cardiovascular Care(2024)10.1093/ehjacc/zuae037

N/A

0DataRank · unranked

17 citations

Albert Lui, Mark Goldstein, Mukund Sudarshan, Andrea Tinsay, Cindy Tsui +16 more

Quantifying impairment and disease severity using AI models trained on healthy subjects

npj Digital Medicine(2024)10.1038/s41746-024-01173-x

N/A

0DataRank · unranked

4 citations

Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily E. Fokas, Anita Venkatesan +5 more

Preference Learning Algorithms Do Not Learn Preference Rankings

arXiv (Cornell University)(2024)10.48550/arxiv.2405.19534

N/A

0DataRank · unranked

0 citations

Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath +2 more

Towards Minimal Targeted Updates of Language Models with Targeted Negative Training

arXiv (Cornell University)(2024)10.48550/arxiv.2406.13660

N/A

0DataRank · unranked

0 citations

Rajesh Ranganath, Arya Tafvizi, Lily H. Zhang

What's the score? Automated Denoising Score Matching for Nonlinear Diffusions

arXiv (Cornell University)(2024)10.48550/arxiv.2407.07998

N/A

0DataRank · unranked

0 citations

Goldstein, Mark, Rajesh Ranganath, Raghav Singhal

Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities

arXiv (Cornell University)(2024)10.48550/arxiv.2411.01053

N/A

0DataRank · unranked

0 citations

Aahlad Puli, Goldstein, Mark, Rajesh Ranganath, Adriel Saporta

Explanations that reveal all through the definition of encoding

arXiv (Cornell University)(2024)10.48550/arxiv.2411.02664

N/A

0DataRank · unranked

0 citations

Nhi Nguyen, Rajesh Ranganath, Aahlad Puli

Transformer-based artificial intelligence on single-cell clinical data for homeostatic mechanism inference and rational biomarker discovery

medRxiv(2025)10.1101/2025.03.24.25324556

N/A

0DataRank · unranked

1 citations

Lily Zhang, Rajesh Ranganath, John M. Higgins, Veronica Tozzo