Output-Oblivious Stochastic Chemical Reaction Networks. - Ben Chugg; Hooman Hashemi; Anne Condon (OPODIS, 2018)

Submodular Stochastic Probing with Prices. - Ben Chugg; Takanori Maehara (CoDIT, 2019)

Composable Computation in Leaderless, Discrete Chemical Reaction Networks. - Hooman Hashemi; Ben Chugg; Anne Condon (DNA, 2020)

Enhancing environmental enforcement with near real-time monitoring: Likelihood-based detection of structural expansion of intensive livestock farms. - Ben Chugg; Brandon R. Anderson; Seiji Eicher; Sandy Lee; Daniel E. Ho (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Simultaneous visibility representations of undirected pairs of graphs. - Ben Chugg; William S. Evans; Kelvin Wong (Comput. Geom., 2021)

Reconciling Risk Allocation and Prevalence Estimation in Public Health Using Batched Bandits. - Ben Chugg; Daniel E. Ho (CoRR, 2021)

Beyond Ads: Sequential Decision-Making Algorithms in Public Policy. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Daniel E. Ho (CoRR, 2021)

Detecting Environmental Violations with Satellite Imagery in Near Real Time: Land Application under the Clean Water Act. - Ben Chugg; Nicolas Rothbacher; Alex Feng; Xiaoqi Long; Daniel E. Ho (CIKM, 2022)

Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Daniel E. Ho (CSLAW, 2022)

Mapping Industrial Poultry Operations at Scale With Deep Learning and Aerial Imagery. - Caleb Robinson; Ben Chugg; Brandon R. Anderson; Juan M. Lavista Ferres; Daniel E. Ho (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection. - Peter Henderson 002; Ben Chugg; Brandon R. Anderson; Kristen M. Altenburger; Alex Turk; John Guyton; Jacob Goldin; Daniel E. Ho (AAAI, 2023)

Entropy Regularization for Population Estimation. - Ben Chugg; Peter Henderson 002; Jacob Goldin; Daniel E. Ho (AAAI, 2023)

Auditing Fairness by Betting. - Ben Chugg; Santiago Cortes-Gomez; Bryan Wilder; Aaditya Ramdas (NeurIPS, 2023)

A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds. - Ben Chugg; Hongjian Wang; Aaditya Ramdas (J. Mach. Learn. Res., 2023)

Time-Uniform Confidence Spheres for Means of Random Vectors. - Ben Chugg; Hongjian Wang; Aaditya Ramdas (Trans. Mach. Learn. Res., 2025)