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ORCIDBarbara E. Engelhardt
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- affiliation: Stanford University, CA, USA
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2020 – today
- 2024
[j18]Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt:
Inverse Reinforcement Learning with Multiple Planning Horizons. RLJ 3: 1138-1167 (2024)- [j17]Siddhartha G. Jena, Archit Verma, Barbara E. Engelhardt:
Answering open questions in biology using spatial genomics and structured methods. BMC Bioinform. 25(1): 291 (2024) - [i25]Syrine Belakaria, Benjamin Letham, Janardhan Rao Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy:
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes. CoRR abs/2407.09739 (2024) - [i24]Ishana Shastri, Shomik Jain, Barbara Engelhardt, Ashia Wilson:
Automating Transparency Mechanisms in the Judicial System Using LLMs: Opportunities and Challenges. CoRR abs/2408.08477 (2024) - [i23]Jiayu Yao, Weiwei Pan, Finale Doshi-Velez, Barbara E. Engelhardt:
Inverse Reinforcement Learning with Multiple Planning Horizons. CoRR abs/2409.18051 (2024) - 2023
- [j16]Michael Minyi Zhang
, Bianca Dumitrascu, Sinead A. Williamson, Barbara E. Engelhardt:
Sequential Gaussian Processes for Online Learning of Nonstationary Functions. IEEE Trans. Signal Process. 71: 1539-1550 (2023) - [c23]Aishwarya Mandyam, Andrew Jones, Jiayu Yao, Krzysztof Laudanski, Barbara E. Engelhardt:
Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations. ML4H@NeurIPS 2023: 323-339 - [e1]Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett:
International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. Proceedings of Machine Learning Research 202, PMLR 2023 [contents] - [i22]Aishwarya Mandyam, Didong Li, Diana Cai, Andrew Jones, Barbara E. Engelhardt:
Kernel Density Bayesian Inverse Reinforcement Learning. CoRR abs/2303.06827 (2023) - [i21]Michael Minyi Zhang, Gregory W. Gundersen, Barbara E. Engelhardt:
Bayesian Non-linear Latent Variable Modeling via Random Fourier Features. CoRR abs/2306.08352 (2023) - [i20]Aishwarya Mandyam, Matthew Jörke, Barbara E. Engelhardt, Emma Brunskill:
Adaptive Interventions with User-Defined Goals for Health Behavior Change. CoRR abs/2311.09483 (2023) - 2022
- [j15]Tiana Fitzgerald, Andrew Jones, Barbara E. Engelhardt:
A Poisson reduced-rank regression model for association mapping in sequencing data. BMC Bioinform. 23(1): 529 (2022) - [c22]Guillaume G. Martinet, Alexander Strzalkowski, Barbara E. Engelhardt:
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction. AISTATS 2022: 8803-8851 - 2021
- [j14]Anqi Wu, Samuel A. Nastase, Christopher Baldassano, Nicholas B. Turk-Browne, Kenneth A. Norman, Barbara E. Engelhardt, Jonathan W. Pillow:
Brain kernel: A new spatial covariance function for fMRI data. NeuroImage 245: 118580 (2021) - [j13]Jonathan Lu, Bianca Dumitrascu, Ian C. McDowell, Brian Jo, Alejandro Barrera, Linda K. Hong, Sarah M. Leichter, Timothy E. Reddy, Barbara E. Engelhardt:
Causal network inference from gene transcriptional time-series response to glucocorticoids. PLoS Comput. Biol. 17(1) (2021) - [c21]Gregory W. Gundersen, Michael Minyi Zhang, Barbara E. Engelhardt:
Latent variable modeling with random features. AISTATS 2021: 1333-1341 - [c20]Aishwarya Mandyam, Elizabeth C. Yoo, Jeff Soules, Krzysztof Laudanski, Barbara E. Engelhardt:
COP-E-CAT: cleaning and organization pipeline for EHR computational and analytic tasks. BCB 2021: 5:1-5:9 - [c19]Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams:
Active multi-fidelity Bayesian online changepoint detection. UAI 2021: 1916-1926 - [i19]Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams:
Active multi-fidelity Bayesian online changepoint detection. CoRR abs/2103.14224 (2021) - [i18]Aishwarya Mandyam, Andrew Jones, Krzysztof Laudanski, Barbara E. Engelhardt:
Nested Policy Reinforcement Learning. CoRR abs/2110.02879 (2021) - [i17]F. William Townes, Barbara E. Engelhardt:
Nonnegative spatial factorization. CoRR abs/2110.06122 (2021) - [i16]Guillaume Martinet, Alexander Strzalkowski, Barbara E. Engelhardt:
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction. CoRR abs/2110.07064 (2021) - 2020
- [j12]Archit Verma, Barbara E. Engelhardt:
A robust nonlinear low-dimensional manifold for single cell RNA-seq data. BMC Bioinform. 21(1): 324 (2020) - [j11]Li-Fang Cheng, Bianca Dumitrascu, Gregory Darnell, Corey Chivers, Michael Draugelis, Kai Li, Barbara E. Engelhardt:
Sparse multi-output Gaussian processes for online medical time series prediction. BMC Medical Informatics Decis. Mak. 20(1): 152 (2020) - [c18]Li-Fang Cheng, Bianca Dumitrascu, Michael Minyi Zhang, Corey Chivers, Michael Draugelis, Kai Li, Barbara E. Engelhardt:
Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes. AISTATS 2020: 4045-4055 - [c17]Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez:
Defining admissible rewards for high-confidence policy evaluation in batch reinforcement learning. CHIL 2020: 1-9 - [i15]Allison June-Barlow Chaney, Archit Verma, Young-Suk Lee, Barbara E. Engelhardt:
Nonparametric Deconvolution Models. CoRR abs/2003.07718 (2020) - [i14]Gregory W. Gundersen, Michael Minyi Zhang, Barbara E. Engelhardt:
Latent variable modeling with random features. CoRR abs/2006.11145 (2020) - [i13]Didong Li, Andrew Jones, Barbara E. Engelhardt:
Probabilistic Contrastive Principal Component Analysis. CoRR abs/2012.07977 (2020)
2010 – 2019
- 2019
- [j10]Bianca Dumitrascu, Gregory Darnell, Julien Ayroles, Barbara E. Engelhardt:
Statistical tests for detecting variance effects in quantitative trait studies. Bioinform. 35(2): 200-210 (2019) - [c16]Grace Guan, Barbara E. Engelhardt:
Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis. MLHC 2019: 271-287 - [c15]Li-Fang Cheng, Niranjani Prasad, Barbara E. Engelhardt:
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units. PSB 2019: 320-331 - [c14]Rebecca Elyanow, Bianca Dumitrascu, Barbara E. Engelhardt, Benjamin J. Raphael:
netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data. RECOMB 2019: 297-298 - [c13]Gregory W. Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt:
End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations. UAI 2019: 945-955 - [i12]Michael Minyi Zhang, Bianca Dumitrascu, Sinead A. Williamson, Barbara E. Engelhardt:
Sequential Gaussian Processes for Online Learning of Nonstationary Functions. CoRR abs/1905.10003 (2019) - [i11]Niranjani Prasad, Barbara E. Engelhardt, Finale Doshi-Velez:
Defining Admissible Rewards for High Confidence Policy Evaluation. CoRR abs/1905.13167 (2019) - [i10]Li-Fang Cheng, Bianca Dumitrascu, Michael Minyi Zhang, Corey Chivers, Michael Draugelis, Kai Li, Barbara E. Engelhardt:
Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes. CoRR abs/1906.00226 (2019) - 2018
- [j9]Ian C. McDowell, Dinesh Manandhar, Christopher M. Vockley, Amy K. Schmid, Timothy E. Reddy, Barbara E. Engelhardt:
Clustering gene expression time series data using an infinite Gaussian process mixture model. PLoS Comput. Biol. 14(1) (2018) - [c12]Bianca Dumitrascu, Karen Feng, Barbara E. Engelhardt:
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits. NeurIPS 2018: 4629-4638 - [c11]Allison June-Barlow Chaney, Brandon M. Stewart, Barbara E. Engelhardt:
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility. RecSys 2018: 224-232 - [i9]Bianca Dumitrascu, Karen Feng, Barbara E. Engelhardt:
PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits. CoRR abs/1805.07458 (2018) - [i8]Li-Fang Cheng, Niranjani Prasad, Barbara E. Engelhardt:
An Optimal Policy for Patient Laboratory Tests in Intensive Care Units. CoRR abs/1808.04679 (2018) - 2017
- [j8]Gregory Darnell, Stoyan Georgiev, Sayan Mukherjee, Barbara E. Engelhardt:
Adaptive Randomized Dimension Reduction on Massive Data. J. Mach. Learn. Res. 18: 140:1-140:30 (2017) - [j7]Xin Li, Yungil Kim, Emily K. Tsang, Joe R. Davis, Farhan N. Damani, Colby Chiang, Gaelen T. Hess, Zachary Zappala, Benjamin J. Strober, Alexandra J. Scott, Amy Li, Andrea Ganna, Michael C. Bassik, Jason D. Merker, François Aguet, Kristin G. Ardlie, Beryl B. Cummings, Ellen T. Gelfand, Gad Getz, Kane Hadley, Robert E. Handsaker, Katherine H. Huang, Seva Kashin, Konrad J. Karczewski, Monkol Lek, Xiao Li, Daniel G. MacArthur, Jared L. Nedzel, Duyen T. Nguyen, Michael S. Noble, Ayellet V. Segrè, Casandra A. Trowbridge, Taru Tukiainen, Nathan S. Abell, Brunilda Balliu, Ruth Barshir, Omer Basha, Alexis J. Battle, Gireesh K. Bogu, Andrew Brown, Christopher D. Brown, Stephane E. Castel, Lin S. Chen, Donald F. Conrad, Nancy J. Cox, Olivier Delaneau, Emmanouil T. Dermitzakis, Barbara E. Engelhardt, Eleazar Eskin, Pedro G. Ferreira, Laure Frésard, Eric R. Gamazon, Diego Garrido-Martín, Ariel D. H. Gewirtz, Genna Gliner, Michael J. Gloudemans, Roderic Guigó, Ira M. Hall, Buhm Han, Yuan He, Farhad Hormozdiari, Cedric Howald, Hae Kyung Im, Brian Jo, Eun Yong Kang, Sarah Kim-Hellmuth, Tuuli Lappalainen, Gen Li, Boxiang Liu, Serghei Mangul, Mark I. McCarthy, Ian C. McDowell, Pejman Mohammadi, Jean Monlong, Stephen B. Montgomery:
The impact of rare variation on gene expression across tissues. Nat. 550(7675): 239-243 (2017) - [c10]Ghassen Jerfel, Mehmet Emin Basbug, Barbara E. Engelhardt:
Dynamic Collaborative Filtering With Compound Poisson Factorization. AISTATS 2017: 738-747 - [c9]Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, Barbara E. Engelhardt:
A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units. UAI 2017 - [i7]Mehmet Emin Basbug, Barbara E. Engelhardt:
Coupled Compound Poisson Factorization. CoRR abs/1701.02058 (2017) - [i6]Niranjani Prasad, Li-Fang Cheng, Corey Chivers, Michael Draugelis, Barbara E. Engelhardt:
A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units. CoRR abs/1704.06300 (2017) - [i5]Allison June-Barlow Chaney, Brandon M. Stewart, Barbara E. Engelhardt:
How Algorithmic Confounding in Recommendation Systems Increases Homogeneity and Decreases Utility. CoRR abs/1710.11214 (2017) - 2016
- [j6]Shiwen Zhao, Chuan Gao, Sayan Mukherjee, Barbara E. Engelhardt:
Bayesian group factor analysis with structured sparsity. J. Mach. Learn. Res. 17: 196:1-196:47 (2016) - [j5]Chuan Gao, Ian C. McDowell, Shiwen Zhao, Christopher D. Brown, Barbara E. Engelhardt:
Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering. PLoS Comput. Biol. 12(7) (2016) - [c8]Mehmet Emin Basbug, Barbara E. Engelhardt:
Hierarchical Compound Poisson Factorization. ICML 2016: 1795-1803 - [i4]Shiwen Zhao, Barbara E. Engelhardt, Sayan Mukherjee, David B. Dunson:
Fast moment estimation for generalized latent Dirichlet models. CoRR abs/1603.05324 (2016) - [i3]Mehmet Emin Basbug, Barbara E. Engelhardt:
Hierarchical Compound Poisson Factorization. CoRR abs/1604.03853 (2016) - [i2]Ghassen Jerfel, Mehmet Emin Basbug, Barbara E. Engelhardt:
Dynamic Collaborative Filtering with Compound Poisson Factorization. CoRR abs/1608.04839 (2016) - 2015
- [i1]Mehmet Emin Basbug, Barbara E. Engelhardt:
Clustering with Beta Divergences. CoRR abs/1510.05491 (2015) - 2013
- [j4]Fantine Mordelet, John Horton, Alexander J. Hartemink, Barbara E. Engelhardt, Raluca Gordân:
Stability selection for regression-based models of transcription factor-DNA binding specificity. Bioinform. 29(13): 117-125 (2013)
2000 – 2009
- 2006
- [c7]Barbara E. Engelhardt, Michael I. Jordan, Steven E. Brenner:
A graphical model for predicting protein molecular function. ICML 2006: 297-304 - 2005
- [j3]Barbara E. Engelhardt, Michael I. Jordan, Kathryn E. Muratore, Steven E. Brenner:
Protein Molecular Function Prediction by Bayesian Phylogenomics. PLoS Comput. Biol. 1(5) (2005) - 2003
- [c6]Eyal Amir, Barbara Engelhardt:
Factored Planning. IJCAI 2003: 929-935 - 2002
- [j2]Benjamin D. Smith, Barbara E. Engelhardt, Darren H. Mutz:
The RADARSAT-MAMM Automated Mission Planner. AI Mag. 23(2): 25-36 (2002) - 2001
- [j1]Russell Knight, Gregg R. Rabideau, Steve A. Chien, Barbara Engelhardt, Rob Sherwood:
Casper: Space Exploration through Continuous Planning. IEEE Intell. Syst. 16(5): 70-75 (2001) - [c5]Rob Sherwood, Andrew Mishkin, Tara A. Estlin, Steve A. Chien, Barbara Engelhardt, Brian K. Cooper, Gregg R. Rabideau:
A Tool for Autonomous Ground-Based Rover Planning. FLAIRS 2001: 73-77 - [c4]Benjamin D. Smith, Barbara E. Engelhardt, Darren H. Mutz:
The RadarSAT-MAMM Automated Mission Planner. IAAI 2001: 35-42 - [c3]Russell Knight, Forest Fisher, Tara A. Estlin, Barbara Engelhardt, Steve A. Chien:
Balancing deliberation and reaction, planning and execution for space robotic applications. IROS 2001: 2131-2139 - 2000
- [c2]Gregg R. Rabideau, Barbara Engelhardt, Steve A. Chien:
Using Generic Preferences to Incrementally Improve Plan Quality. AIPS 2000: 236-245 - [c1]Barbara Engelhardt, Steve A. Chien:
Empirical Evaluation of Local Search Methods for Adapting Planning Policies in a Stochastic Environment. Local Search for Planning and Scheduling 2000: 108-119
Coauthor Index
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last updated on 2024-11-25 23:42 CET by the dblp team
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