Likelihoods for fixed rank nomination networks. - Peter Hoff; Bailey K. Fosdick; Alexander Volfovsky; Katherine Stovel (Netw. Sci., 2013)

Networks. - Elizabeth L. Ogburn; Alexander Volfovsky (Handbook of Big Data, 2016)

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. - Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky; Tianyu Wang 008 (CoRR, 2017)

Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference. - Awa Dieng; Yameng Liu; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (CoRR, 2018)

SMOGS: Social Network Metrics of Game Success. - Fan Bu; Sonia Xu; Katherine A. Heller; Alexander Volfovsky (AISTATS, 2019)

Interpretable Almost-Exact Matching for Causal Inference. - Awa Dieng; Yameng Liu; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2019)

Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise. - Heather Mathews; Vaishakhi Mayya; Alexander Volfovsky; Galen Reeves (CAMSAP, 2019)

The Geometry of Community Detection via the MMSE Matrix. - Galen Reeves; Vaishakhi Mayya; Alexander Volfovsky (ISIT, 2019)

Interpretable Almost Matching Exactly With Instrumental Variables. - M. Usaid Awan; Yameng Liu; Marco Morucci; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (UAI, 2019)

Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. - M. Usaid Awan; Marco Morucci; Vittorio Orlandi; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2020)

Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. - Marco Morucci; Vittorio Orlandi; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (UAI, 2020)

dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference. - Neha R. Gupta; Vittorio Orlandi; Chia-Rui Chang; Tianyu Wang 008; Marco Morucci; Pritam Dey; Thomas J. Howell; Xian Sun; Angikar Ghosal; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (CoRR, 2021)

Author Clustering and Topic Estimation for Short Texts. - Graham Tierney; Christopher Bail; Alexander Volfovsky (CoRR, 2021)

FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. - Tianyu Wang 008; Marco Morucci; M. Usaid Awan; Yameng Liu; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (J. Mach. Learn. Res., 2021)

Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It. - Harsh Parikh; Kentaro Hoffman; Haoqi Sun; Wendong Ge; Jin Jing; Rajesh Amerineni; Lin Liu; Jimeng Sun 001; Sahar Zafar; Aaron Struck; Alexander Volfovsky; Cynthia Rudin; et al. (CoRR, 2022)

Neighborhood Adaptive Estimators for Causal Inference under Network Interference. - Alexandre Belloni; Fei Fang; Alexander Volfovsky (CoRR, 2022)

MALTS: Matching After Learning to Stretch. - Harsh Parikh; Cynthia Rudin; Alexander Volfovsky (J. Mach. Learn. Res., 2022)

Experimental Designs for Heteroskedastic Variance. - Justin Weltz; Tanner Fiez; Alexander Volfovsky; Eric Laber; Blake Mason; Houssam Nassif; Lalit Jain (NeurIPS, 2023)

Variable importance matching for causal inference. - Quinn Lanners; Harsh Parikh; Alexander Volfovsky; Cynthia Rudin; David Page (UAI, 2023)

From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. - Quinn Lanners; Harsh Parikh; Alexander Volfovsky; Cynthia Rudin; David Page (CoRR, 2023)

A Double Machine Learning Approach to Combining Experimental and Observational Data. - Marco Morucci; Vittorio Orlandi; Harsh Parikh; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (CoRR, 2023)

Estimating Trustworthy and Safe Optimal Treatment Regimes. - Harsh Parikh; Quinn Lanners; Zade Akras; Sahar F. Zafar; M. Brandon Westover; Cynthia Rudin; Alexander Volfovsky (CoRR, 2023)

Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference. - Travis Seale-Carlisle; Saksham Jain; Courtney Lee; Caroline Levenson; Swathi Ramprasad; Brandon Garrett; Sudeepa Roy 001; Cynthia Rudin; Alexander Volfovsky (AAAI, 2024)

Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. - Srikar Katta; Harsh Parikh; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2024)

Safe and Interpretable Estimation of Optimal Treatment Regimes. - Harsh Parikh; Quinn Lanners; Zade Akras; Sahar Zafar; M. Brandon Westover; Cynthia Rudin; Alexander Volfovsky (AISTATS, 2024)

Hidden Population Estimation with Indirect Inference and Auxiliary Information. - Justin Weltz; Eric Laber; Alexander Volfovsky (UAI, 2024)

Scalable Policy Maximization Under Network Interference. - Aidan Gleich; Eric Laber; Alexander Volfovsky (CoRR, 2025)

Data Fusion for Partial Identification of Causal Effects. - Quinn Lanners; Cynthia Rudin; Alexander Volfovsky; Harsh Parikh (CoRR, 2025)