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Rajesh Ranganath

New York University

Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations


Mar 02, 2021
Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath

* Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 
* 15 pages, 3 figures, Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 

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Causal Estimation with Functional Confounders


Feb 17, 2021
Aahlad Puli, Adler J. Perotte, Rajesh Ranganath

* 17 pages, 7 figures, 2 tables 

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X-CAL: Explicit Calibration for Survival Analysis


Jan 13, 2021
Mark Goldstein, Xintian Han, Aahlad Puli, Adler J. Perotte, Rajesh Ranganath


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Probabilistic Machine Learning for Healthcare


Sep 23, 2020
Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath

* Annual Reviews of Biomedical Data Science 2021 

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Deep Direct Likelihood Knockoffs


Jul 31, 2020
Mukund Sudarshan, Wesley Tansey, Rajesh Ranganath


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Overfitting and Optimization in Offline Policy Learning


Jun 27, 2020
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna


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The Counterfactual $χ$-GAN


Jan 09, 2020
Amelia J. Averitt, Natnicha Vanitchanant, Rajesh Ranganath, Adler J. Perotte

* 9 pages; 3 figures; under review 

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Energy-Inspired Models: Learning with Sampler-Induced Distributions


Oct 31, 2019
Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath


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Population Predictive Checks


Aug 08, 2019
Rajesh Ranganath, David M. Blei


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Generalized Control Functions via Variational Decoupling


Jul 08, 2019
Aahlad Manas Puli, Rajesh Ranganath

* 19 pages 

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Reproducibility in Machine Learning for Health


Jul 02, 2019
Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini

* Presented at the ICLR 2019 Reproducibility in Machine Learning Workshop 

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Adversarial Examples for Electrocardiograms


Jun 04, 2019
Xintian Han, Yuxuan Hu, Luca Foschini, Larry Chinitz, Lior Jankelson, Rajesh Ranganath


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Kernelized Complete Conditional Stein Discrepancy


Apr 13, 2019
Raghav Singhal, Saad Lahlou, Rajesh Ranganath


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ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission


Apr 11, 2019
Kexin Huang, Jaan Altosaar, Rajesh Ranganath


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The Random Conditional Distribution for Higher-Order Probabilistic Inference


Mar 25, 2019
Zenna Tavares, Xin Zhang, Edgar Minaysan, Javier Burroni, Rajesh Ranganath, Armando Solar Lezama

* 12 pages 

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Support and Invertibility in Domain-Invariant Representations


Mar 21, 2019
Fredrik D. Johansson, David Sontag, Rajesh Ranganath


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The Variational Predictive Natural Gradient


Mar 07, 2019
Da Tang, Rajesh Ranganath

* 12 pages, 4 figures 

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Soft Constraints for Inference with Declarative Knowledge


Jan 16, 2019
Zenna Tavares, Javier Burroni, Edgar Minaysan, Armando Solar Lezama, Rajesh Ranganath


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Multiple Causal Inference with Latent Confounding


Aug 07, 2018
Rajesh Ranganath, Adler Perotte


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Noisin: Unbiased Regularization for Recurrent Neural Networks


Jul 13, 2018
Adji B. Dieng, Rajesh Ranganath, Jaan Altosaar, David M. Blei

* In Proceedings of the International Conference on Machine Learning, 2018 

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Opportunities in Machine Learning for Healthcare


Jun 05, 2018
Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath

* Corrected preprint footer 

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Operator Variational Inference


Mar 15, 2018
Rajesh Ranganath, Jaan Altosaar, Dustin Tran, David M. Blei

* Appears in Neural Information Processing Systems, 2016 

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Variational Sequential Monte Carlo


Feb 21, 2018
Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei


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Variational Inference via $χ$-Upper Bound Minimization


Nov 12, 2017
Adji B. Dieng, Dustin Tran, Rajesh Ranganath, John Paisley, David M. Blei

* Neural Information Processing Systems, 2017 

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Hierarchical Implicit Models and Likelihood-Free Variational Inference


Nov 05, 2017
Dustin Tran, Rajesh Ranganath, David M. Blei

* Appears in Neural Information Processing Systems, 2017 

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Proximity Variational Inference


May 24, 2017
Jaan Altosaar, Rajesh Ranganath, David M. Blei


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Correlated Random Measures


Nov 09, 2016
Rajesh Ranganath, David Blei


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Deep Survival Analysis


Sep 18, 2016
Rajesh Ranganath, Adler Perotte, Noémie Elhadad, David Blei

* Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, CA 

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Hierarchical Variational Models


May 30, 2016
Rajesh Ranganath, Dustin Tran, David M. Blei

* Appears in International Conference on Machine Learning, 2016 

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