Barbara E. Engelhardt

According to our database1, Barbara E. Engelhardt authored at least 27 papers between 2002 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2020
Latent variable modeling with random features.
CoRR, 2020

Nonparametric Deconvolution Models.
CoRR, 2020

Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Defining Admissible Rewards for High Confidence Policy Evaluation.
CoRR, 2019

Sequential Gaussian Processes for Online Learning of Nonstationary Functions.
CoRR, 2019

Statistical tests for detecting variance effects in quantitative trait studies.
Bioinform., 2019

End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data.
Proceedings of the Research in Computational Molecular Biology, 2019

An Optimal Policy for Patient Laboratory Tests in Intensive Care Units.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis.
Proceedings of the Machine Learning for Healthcare Conference, 2019

2018
Clustering gene expression time series data using an infinite Gaussian process mixture model.
PLoS Computational Biology, 2018

How algorithmic confounding in recommendation systems increases homogeneity and decreases utility.
Proceedings of the 12th ACM Conference on Recommender Systems, 2018

PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Adaptive Randomized Dimension Reduction on Massive Data.
J. Mach. Learn. Res., 2017

Coupled Compound Poisson Factorization.
CoRR, 2017

A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Dynamic Collaborative Filtering With Compound Poisson Factorization.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering.
PLoS Computational Biology, 2016

Bayesian group factor analysis with structured sparsity.
J. Mach. Learn. Res., 2016

Fast moment estimation for generalized latent Dirichlet models.
CoRR, 2016

Hierarchical Compound Poisson Factorization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Clustering with Beta Divergences.
CoRR, 2015

2013
Stability selection for regression-based models of transcription factor-DNA binding specificity.
Bioinform., 2013

2006
A graphical model for predicting protein molecular function.
Proceedings of the Machine Learning, 2006

2005
Protein Molecular Function Prediction by Bayesian Phylogenomics.
PLoS Computational Biology, 2005

2002
The RADARSAT-MAMM Automated Mission Planner.
AI Magazine, 2002


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