Shachi Deshpande

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Volodymyr KuleshovCornell TechVerified email at stanford.edu
Kaiwen WangComputer Science PhD at Cornell TechVerified email at cornell.edu
Daniel DoerrHeinrich Heine University DüsseldorfVerified email at hhu.de
Bernard M.E. MoretISCB Fellow, Professor emeritus, Computer & Communication Sciences, EPFLVerified email at epfl.ch
Luis Antonio Brasil KowadaUFFVerified email at ic.uff.br
Jens StoyeBielefeld University, GermanyVerified email at uni-bielefeld.de
Eloi AraujoUniversidade Federal de Mato Grosso do SulVerified email at ufms.br

Shachi Deshpande

Verified email at cornell.edu - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Calibrated and sharp uncertainties in deep learning via density estimation V Kuleshov, S Deshpande International Conference on Machine Learning, 11683-11693, 2022	22	2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies S Deshpande, K Wang, D Sreenivas, Z Li, V Kuleshov Advances in Neural Information Processing Systems 35, 10931-10944, 2022	9	2022
Online Calibrated and Conformal Prediction Improves Bayesian Optimization S Deshpande, C Marx, V Kuleshov International Conference on Artificial Intelligence and Statistics, 1450-1458, 2024	5*	2024
New Genome Similarity Measures based on Conserved Gene Adjacencies D Doerr, LAB Kowada, E Araujo, S Deshpande, S Dantas, BME Moret, ... Journal of Computational Biology 24 (6), 616-634, 2017	3	2017
Adversarial Calibrated Regression for Online Decision Making V Kuleshov, S Deshpande arXiv preprint arXiv:2302.12196, 2023	1*	2023
Calibrated Propensity Scores for Causal Effect Estimation S Deshpande, V Kuleshov arXiv preprint arXiv:2306.00382, 2023		2023

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