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BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data


Sep 12, 2022
Karine Tung, Steven De La Torre, Mohamed El Mistiri, Rebecca Braga De Braganca, Eric Hekler, Misha Pavel, Daniel Rivera, Pedja Klasnja, Donna Spruijt-Metz, Benjamin M. Marlin

* Accepted at IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2022 

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Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning


Feb 08, 2022
Meet P. Vadera, Adam D. Cobb, Brian Jalaian, Benjamin M. Marlin

* Preprint. Work in progress 

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Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems


Dec 03, 2021
Meet P. Vadera, Benjamin M. Marlin


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Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series


Jul 23, 2021
Satya Narayan Shukla, Benjamin M. Marlin


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Post-hoc loss-calibration for Bayesian neural networks


Jun 13, 2021
Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin

* Accepted to Conference on Uncertainty in AI (UAI) '21 

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Multi-Time Attention Networks for Irregularly Sampled Time Series


Jan 25, 2021
Satya Narayan Shukla, Benjamin M. Marlin

* Accepted at International Conference on Learning Representations (ICLR) 2021 

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A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series


Jan 05, 2021
Satya Narayan Shukla, Benjamin M. Marlin

* Presented at NeurIPS 2020 Workshop: ML Retrospectives, Surveys & Meta-Analyses (ML-RSA) 

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A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance


Nov 30, 2020
Satya Narayan Shukla, Benjamin M. Marlin


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Learning from Irregularly-Sampled Time Series: A Missing Data Perspective


Aug 17, 2020
Steven Cheng-Xian Li, Benjamin M. Marlin


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


Jul 08, 2020
Meet P. Vadera, Adam D. Cobb, Brian Jalaian, Benjamin M. Marlin

* Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning 

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