Jennifer Brennan

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Citations	109	108
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Zachary TatlockUniversity of WashingtonVerified email at cs.washington.edu
Mike HePrinceton UniversityVerified email at princeton.edu
Jared RoeschOctoML IncVerified email at cs.uw.edu
Tianqi ChenCarnegie Mellon UniversityVerified email at cmu.edu
Altan HaanPhD Student, UC Berkeley EECSVerified email at eecs.berkeley.edu
Marisa KirisamePHD Candidate, University of UtahVerified email at cs.utah.edu
Kevin JamiesonAssociate Professor, University of WashingtonVerified email at cs.washington.edu
Jean Pouget-AbadieGoogle ResearchVerified email at google.com
Vahab MirrokniGoogle Fellow, VP, Google ResearchVerified email at google.com
Ramya Korlakai VinayakAssistant Professor, UW-MadisonVerified email at ece.wisc.edu
Yi-Chieh WuHarvey Mudd CollegeVerified email at cs.hmc.edu
Lalit JainUniversity of WashingtonVerified email at uw.edu
Harsh VermaTruvetaVerified email at truveta.com
John ThickstunPostdoc, Stanford UniversityVerified email at stanford.edu
Kendall LowreyUniversity of WashingtonVerified email at cs.washington.edu
Lauren B WilnerUniversity of WashingtonVerified email at uw.edu
Ben EvansNew York UniversityVerified email at nyu.edu
Nicholas J KassebaumUniversity of Washington, Seattle, WA, USAVerified email at uw.edu
Josue NassarOptum AIVerified email at optum.com
Peng ZhengUniversity of WashingtonVerified email at uw.edu

Jennifer Brennan

Google Research

Verified email at google.com - Homepage

experimental design machine learning causal inference multiple hypothesis testing


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Dynamic tensor rematerialization M Kirisame, S Lyubomirsky, A Haan, J Brennan, M He, J Roesch, T Chen, ... arXiv preprint arXiv:2006.09616, 2020	72	2020
Estimating the number and effect sizes of non-null hypotheses J Brennan, RK Vinayak, K Jamieson International Conference on Machine Learning, 1123-1133, 2020	9	2020
Reconciliation feasibility in the presence of gene duplication, loss, and coalescence with multiple individuals per species J Rogers, A Fishberg, N Youngs, YC Wu BMC bioinformatics 18, 1-10, 2017	8	2017
Cluster randomized designs for one-sided bipartite experiments J Brennan, V Mirrokni, J Pouget-Abadie Advances in Neural Information Processing Systems 35, 37962-37974, 2022	7	2022
Rethinking evaluation methodology for audio-to-score alignment J Thickstun, J Brennan, H Verma arXiv preprint arXiv:2009.14374, 2020	4	2020
A Study of" Symbiosis Bias" in A/B Tests of Recommendation Algorithms D Holtz, J Brennan, J Pouget-Abadie arXiv preprint arXiv:2309.07107, 2023	2	2023
Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design J Brennan, L Jain, S Garman, AE Donnelly, ES Wright, K Jamieson PLOS Computational Biology 18 (7), e1010311, 2022	2	2022
BAM: Bayes with adaptive memory J Nassar, J Brennan, B Evans, K Lowrey arXiv preprint arXiv:2202.02405, 2022	2	2022
Analysis and methods to mitigate effects of under-reporting in count data J Brennan, M Bannick, N Kassebaum, L Wilner, A Thomson, A Aravkin, ... arXiv preprint arXiv:2109.12247, 2021	2	2021
Causal estimation of user learning in personalized systems E Munro, D Jones, J Brennan, R Nelet, V Mirrokni, J Pouget-Abadie Proceedings of the 24th ACM Conference on Economics and Computation, 992-1016, 2023	1	2023
Experimental Design with Scientific Applications J Brennan University of Washington, 2022		2022
Experimental Design to Identify Antibiotic Synergy J Brennan, L Jain, S Garman, AE Donnelly, ES Wright, K Jamieson

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