| 2025 | AAAI | Local Causal Discovery for Structural Evidence of Direct Discrimination. | Jacqueline R. M. A. Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang |
| 2025 | AISTATS | Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits. | Brian M. Cho, Dominik Meier, Kyra Gan, Nathan Kallus |
| 2025 | KDD | CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies. | Brian M. Cho, Ana-Roxana Pop, Kyra Gan, Sam Corbett-Davies, Israel Nir, Ariel Evnine, Nathan Kallus |
| 2025 | UAI | LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery. | Sujai Hiremath, Promit Ghosal, Kyra Gan |
| 2024 | AISTATS | Contextual Bandits with Budgeted Information Reveal. | Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy |
| 2024 | ICML | Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams. | Brian Cho, Kyra Gan, Nathan Kallus |
| 2024 | ICML | Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters. | Brian M. Cho, Yaroslav Mukhin, Kyra Gan, Ivana Malenica |
| 2024 | UAI | Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. | Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang |
| 2021 | AISTATS | Causal Inference with Selectively Deconfounded Data. | Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur |