( en | de | ru )

 

Disambiguation of "Ranganath, Rajesh"

Author of the publication

copydeleteadd this publication to your clipboard
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models.

, , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 12427-12436. PMLR, (2021)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Ranganath Gopalakrishnan

Rajesh Saiju

Hybrid Power System Modelling - Simulation and Energy Management Unit Development. Uni Kassel, (2008)

Rajesh Chitta

Rajesh Saiju

Rajesh Narasimha

 

Other publications of authors with the same name

Deterministic Annealing for Stochastic Variational Inference., , , and . CoRR, (2014)Unsupervised learning of hierarchical representations with convolutional deep belief networks., , , and . Commun. ACM, 54 (10): 95-103 (2011)Noisin: Unbiased Regularization for Recurrent Neural Networks., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 1251-1260. PMLR, (2018)A dynamic risk score for early prediction of cardiogenic shock using machine learning., , , , , , , , , and 11 other author(s). CoRR, (2023)A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients., , , , , , , , , and 14 other author(s). npj Digit. Medicine, (2020)Support and Invertibility in Domain-Invariant Representations., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 527-536. PMLR, (2019)The Counterfactual χ-GAN: Finding comparable cohorts in observational health data., , , and . J. Biomed. Informatics, (2020)An Effective Meaningful Way to Evaluate Survival Models., , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 28244-28276. PMLR, (2023)CONTRA: Contrarian statistics for controlled variable selection., , , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 1900-1908. PMLR, (2021)Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation., , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 8925-8953. PMLR, (2023)