Jacqueline R. M. A. Maasch

15 papers A* 4A 1Misc 1Journal 9

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Compositional Causal Reasoning Evaluation in Language Models. ICML Jacqueline R. M. A. Maasch, Alihan Hüyük, Xinnuo Xu, Aditya V. Nori, Javier González
2025	J	`jnl`	Compositional Causal Reasoning Evaluation in Language Models. CoRR Jacqueline R. M. A. Maasch, Alihan Hüyük, Xinnuo Xu, Aditya V. Nori, Javier González
2025	J	`jnl`	Extracting Post-Acute Sequelae of SARS-CoV-2 Infection Symptoms from Clinical Notes via Hybrid Natural Language Processing. CoRR Zilong Bai, Zihan Xu, Cong Sun, Chengxi Zang, H. Timothy Bunnell, Catherine Sinfield, Jacqueline R. M. A. Maasch, Aaron Thomas Martinez, L. Charles Bailey, Mark G. Weiner, Thomas R. Campion Jr., Thomas Carton, Christopher B. Forrest, Rainu Kaushal, Fei Wang, Yifan Peng
2025	A*	`conf`	Local Causal Discovery for Structural Evidence of Direct Discrimination. AAAI Jacqueline R. M. A. Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang
2025	J	`jnl`	Probabilistic Graphical Models: A Concise Tutorial. CoRR Jacqueline R. M. A. Maasch, Willie Neiswanger, Stefano Ermon, Volodymyr Kuleshov
2025	A*	`conf`	Reasoning Elicitation in Language Models via Counterfactual Feedback. ICLR Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier González
2024	J	`jnl`	Hybrid Global Causal Discovery with Local Search. CoRR Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan
2024	A*	`conf`	Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models. NeurIPS Sujai Hiremath, Jacqueline R. M. A. Maasch, Mengxiao Gao, Promit Ghosal, Kyra Gan
2024	J	`jnl`	Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data. npj Digit. Medicine Chang Su, Yu Hou, Jielin Xu, Zhenxing Xu, Manqi Zhou, Alison Ke, Haoyang Li, Jie Xu, Matthew Brendel, Jacqueline R. M. A. Maasch, Zilong Bai, Haotan Zhang, Yingying Zhu, Molly C. Cincotta, Xinghua Shi, Claire Henchcliffe, James B. Leverenz, Jeffrey Cummings, Michael S. Okun, Jiang Bian, Feixiong Cheng, Fei Wang
2024	J	`jnl`	Local Causal Discovery for Structural Evidence of Direct Discrimination. CoRR Jacqueline R. M. A. Maasch, Kyra Gan, Violet Chen, Agni Orfanoudaki, Nil-Jana Akpinar, Fei Wang
2024	A	`conf`	Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. UAI Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang
2024	J	`jnl`	Reasoning Elicitation in Language Models via Counterfactual Feedback. CoRR Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier González
2023	J	`jnl`	Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs. CoRR Jacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang
2022	Misc	`conf`	Comprehensively modeling heterogeneous symptom progression for Parkinson's disease subtyping. AMIA Chang Su, Yu Hou, Jielin Xu, Matthew Brendel, Jacqueline R. M. A. Maasch, Zilong Bai, Yingying Zhu, Claire Henchcliffe, Feixiong Cheng, Fei Wang
2022	J	`jnl`	Regularized Data Programming with Bayesian Priors. CoRR Jacqueline R. M. A. Maasch, Hao Zhang, Qian Yang, Fei Wang, Volodymyr Kuleshov