Estimating the Number and Effect Sizes of Non-null Hypotheses. - Jennifer Brennan; Ramya Korlakai Vinayak; Kevin Jamieson 001 (ICML, 2020)

Rethinking Evaluation Methodology for Audio-to-Score Alignment. - John Thickstun; Jennifer Brennan; Harsh Verma (CoRR, 2020)

Dynamic Tensor Rematerialization. - Marisa Kirisame; Steven Lyubomirsky; Altan Haan; Jennifer Brennan; Mike He; Jared Roesch; Tianqi Chen 001; Zachary Tatlock (ICLR, 2021)

BAM: Bayes with Adaptive Memory. - Josue Nassar; Jennifer Rogers Brennan; Ben Evans; Kendall Lowrey (ICLR, 2022)

Cluster Randomized Designs for One-Sided Bipartite Experiments. - Jennifer Brennan; Vahab Mirrokni; Jean Pouget-Abadie (NeurIPS, 2022)

Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design. - Jennifer Brennan; Lalit Jain; Sofia Garman; Ann E. Donnelly; Erik Scott Wright; Kevin G. Jamieson (PLoS Comput. Biol., 2022)

Experimental Design with Scientific Applications - Jennifer Brennan (2022)

Causal Estimation of User Learning in Personalized Systems. - Evan Munro; David Jones; Jennifer Brennan; Roland Nelet; Vahab Mirrokni; Jean Pouget-Abadie (EC, 2023)

Country-diverted experiments for mitigation of network effects. - Lina Lin; Changping Meng; Jennifer Brennan; Jean Pouget-Abadie; Ningren Han; Shuchao Bi; Yajun Peng (RecSys, 2024)

Reducing Symbiosis Bias through Better A/B Tests of Recommendation Algorithms. - Jennifer Brennan; Yahu Cong; Yiwei Yu; Lina Lin; Yajun Peng; Changping Meng; Ningren Han; Jean Pouget-Abadie; David M. Holtz (WWW, 2025)