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Disambiguation of "Vadera, Meet P."

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URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks.

, , , and . CoRR, (2020)

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Michael Meetz

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Other publications of authors with the same name

Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty., and . CoRR, (2019)On Uncertainty and Robustness in Large-Scale Intelligent Data Fusion Systems., , , , , , , , , and 4 other author(s). CogMI, page 82-91. IEEE, (2020)Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning., , , and . CoRR, (2022)Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification., , , and . CoRR, (2020)URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks., , , and . CoRR, (2020)Post-hoc loss-calibration for Bayesian neural networks., , , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1403-1412. AUAI Press, (2021)URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods., , , , , and . MLSys, mlsys.org, (2022)Poster Abstract: Investigating Fusion-Based Deep Learning Architectures for Smoking Puff Detection., and . CHASE, page 11-12. IEEE, (2019)Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks., , and . UAI, volume 124 of Proceedings of Machine Learning Research, page 719-728. AUAI Press, (2020)Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems., and . CogMI, page 252-261. IEEE, (2021)