Poster Abstract: Investigating Fusion-Based Deep Learning Architectures for Smoking Puff Detection. - Benjamin M. Marlin; Meet P. Vadera (CHASE, 2019)

Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty. - Meet P. Vadera; Benjamin M. Marlin (CoRR, 2019)

On Uncertainty and Robustness in Large-Scale Intelligent Data Fusion Systems. - Benjamin M. Marlin; Tarek F. Abdelzaher; Gabriela F. Ciocarlie; Adam D. Cobb; Mark Dennison; Brian Jalaian; Lance M. Kaplan; Tiffany Raber; Adrienne Raglin; Piyush K. Sharma; Mani B. Srivastava; Theron Trout; et al. (CogMI, 2020)

Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks. - Meet P. Vadera; Brian Jalaian; Benjamin M. Marlin (UAI, 2020)

Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification. - Meet P. Vadera; Satya Narayan Shukla; Brian Jalaian; Benjamin M. Marlin (CoRR, 2020)

URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks. - Meet P. Vadera; Adam D. Cobb; Brian Jalaian; Benjamin M. Marlin (CoRR, 2020)

Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems. - Meet P. Vadera; Benjamin M. Marlin (CogMI, 2021)

Post-hoc loss-calibration for Bayesian neural networks. - Meet P. Vadera; Soumya Ghosh; Kenney Ng; Benjamin M. Marlin (UAI, 2021)

Uncertainty Quantification Using Query-Based Object Detectors. - Meet P. Vadera; Colin Samplawski; Benjamin M. Marlin (ECCV Workshops (8), 2022)

URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods. - Meet P. Vadera; Jinyang Li 004; Adam D. Cobb; Brian Jalaian; Tarek F. Abdelzaher; Benjamin M. Marlin (MLSys, 2022)

Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning. - Meet P. Vadera; Adam D. Cobb; Brian Jalaian; Benjamin M. Marlin (CoRR, 2022)