| 2025 | EMNLP | Learning Is Not A Race: Improving Retrieval in Language Models via Equal Learning. | Wanqian Yang, Aahlad Manas Puli, Rajesh Ranganath |
| 2025 | ICLR | Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do. | Yoav Wald, Mark Goldstein, Yonathan Efroni, Wouter A. C. van Amsterdam, Rajesh Ranganath |
| 2025 | ICML | A General Framework for Inference-time Scaling and Steering of Diffusion Models. | Raghav Singhal, Zachary Horvitz, Ryan Teehan, Mengye Ren, Zhou Yu, Kathleen McKeown, Rajesh Ranganath |
| 2025 | ICML | Preference learning made easy: Everything should be understood through win rate. | Lily H. Zhang, Rajesh Ranganath |
| 2024 | ICML | Stochastic Interpolants with Data-Dependent Couplings. | Michael S. Albergo, Mark Goldstein, Nicholas Matthew Boffi, Rajesh Ranganath, Eric Vanden-Eijnden |
| 2024 | ICML | What's the score? Automated Denoising Score Matching for Nonlinear Diffusions. | Raghav Singhal, Mark Goldstein, Rajesh Ranganath |
| 2024 | ICML | Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction. | Chen-Yu Yen, Raghav Singhal, Umang Sharma, Rajesh Ranganath, Sumit Chopra, Lerrel Pinto |
| 2023 | AAAI | Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection. | Lily H. Zhang, Rajesh Ranganath |
| 2023 | AISTATS | Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation. | Neil Jethani, Adriel Saporta, Rajesh Ranganath |
| 2023 | AISTATS | DIET: Conditional independence testing with marginal dependence measures of residual information. | Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath |
| 2023 | ICLR | Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions. | Raghav Singhal, Mark Goldstein, Rajesh Ranganath |
| 2023 | ICML | An Effective Meaningful Way to Evaluate Survival Models. | Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner |
| 2022 | ICLR | FastSHAP: Real-Time Shapley Value Estimation. | Neil Jethani, Mukund Sudarshan, Ian Connick Covert, Su-In Lee, Rajesh Ranganath |
| 2022 | ICLR | Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations. | Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath |
| 2022 | ICML | Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets. | Lily H. Zhang, Veronica Tozzo, John M. Higgins, Rajesh Ranganath |
| 2021 | AISTATS | Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations. | Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath |
| 2021 | AISTATS | CONTRA: Contrarian statistics for controlled variable selection. | Mukund Sudarshan, Aahlad Manas Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath |
| 2021 | ICML | Offline Contextual Bandits with Overparameterized Models. | David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna |
| 2021 | ICML | Understanding Failures in Out-of-Distribution Detection with Deep Generative Models. | Lily H. Zhang, Mark Goldstein, Rajesh Ranganath |
| 2020 | AMIA | Adversarially-Learned Balancing Weights for Causal Inference. | Amelia J. Averitt, Natnicha Vanitchanant, Rajesh Ranganath, Adler J. Perotte |
| 2020 | AMIA | Deep Survival Analysis: The Impact of Feature Missingness. | Shreyas Bhave, Xintian Han, Rajesh Ranganath, Adler J. Perotte |
| 2019 | AISTATS | Support and Invertibility in Domain-Invariant Representations. | Fredrik D. Johansson, David A. Sontag, Rajesh Ranganath |
| 2019 | ICLR | Revisiting Auxiliary Latent Variables in Generative Models. | Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath |
| 2019 | ICLR | Reproducibility in Machine Learning for Health. | Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini |
| 2019 | ICML | The Variational Predictive Natural Gradient. | Da Tang, Rajesh Ranganath |
| 2019 | ICML | Predicate Exchange: Inference with Declarative Knowledge. | Zenna Tavares, Javier Burroni, Edgar Minasyan, Armando Solar-Lezama, Rajesh Ranganath |
| 2018 | AISTATS | Proximity Variational Inference. | Jaan Altosaar, Rajesh Ranganath, David M. Blei |
| 2018 | AISTATS | Variational Sequential Monte Carlo. | Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei |
| 2018 | ICML | Noisin: Unbiased Regularization for Recurrent Neural Networks. | Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar, David M. Blei |
| 2018 | UAI | Max-margin learning with the Bayes factor. | Rahul G. Krishnan, Arjun Khandelwal, Rajesh Ranganath, David A. Sontag |
| 2016 | AISTATS | Variational Tempering. | Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei |
| 2016 | ICML | Hierarchical Variational Models. | Rajesh Ranganath, Dustin Tran, David M. Blei |
| 2015 | AISTATS | Deep Exponential Families. | Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei |
| 2015 | RecSys | Dynamic Poisson Factorization. | Laurent Charlin, Rajesh Ranganath, James McInerney, David M. Blei |
| 2015 | UAI | The Survival Filter: Joint Survival Analysis with a Latent Time Series. | Rajesh Ranganath, Adler J. Perotte, Nomie Elhadad, David M. Blei |
| 2014 | AISTATS | Bayesian Nonparametric Poisson Factorization for Recommendation Systems. | Prem Gopalan, Francisco J. R. Ruiz, Rajesh Ranganath, David M. Blei |
| 2014 | AISTATS | Black Box Variational Inference. | Rajesh Ranganath, Sean Gerrish, David M. Blei |
| 2013 | ICML | An Adaptive Learning Rate for Stochastic Variational Inference. | Rajesh Ranganath, Chong Wang, David M. Blei, Eric P. Xing |
| 2009 | EMNLP | It's Not You, it's Me: Detecting Flirting and its Misperception in Speed-Dates. | Rajesh Ranganath, Daniel Jurafsky, Daniel A. McFarland |
| 2009 | ICML | Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. | Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng |
| 2009 | NAACL | Extracting Social Meaning: Identifying Interactional Style in Spoken Conversation. | Daniel Jurafsky, Rajesh Ranganath, Daniel A. McFarland |