A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning. - Lesia Semenova; Cynthia Rudin (CoRR, 2019)

Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges. - Cynthia Rudin; Chaofan Chen; Zhi Chen 009; Haiyang Huang 003; Lesia Semenova; Chudi Zhong (CoRR, 2021)

Multitask Learning for Citation Purpose Classification. - Alex Oesterling; Angikar Ghosal; Haoyang Yu; Rui Xin 002; Yasa Baig; Lesia Semenova; Cynthia Rudin (CoRR, 2021)

On the Existence of Simpler Machine Learning Models. - Lesia Semenova; Cynthia Rudin; Ronald Parr (FAccT, 2022)

A Path to Simpler Models Starts With Noise. - Lesia Semenova; Harry Chen; Ronald Parr; Cynthia Rudin (NeurIPS, 2023)

ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges. - Dennis Tang; Frank Willard; Ronan Tegerdine; Luke Triplett; Jon Donnelly; Luke Moffett; Lesia Semenova; Alina Jade Barnett; Jin Jing; Cynthia Rudin; M. Brandon Westover (CoRR, 2023)

Position: Amazing Things Come From Having Many Good Models. - Cynthia Rudin; Chudi Zhong; Lesia Semenova; Margo I. Seltzer; Ronald Parr; Jiachang Liu 001; Srikar Katta; Jon Donnelly; Harry Chen; Zachery Boner (ICML, 2024)

Using Noise to Infer Aspects of Simplicity Without Learning. - Zachery Boner; Harry Chen; Lesia Semenova; Ronald Parr; Cynthia Rudin (NeurIPS, 2024)

Amazing Things Come From Having Many Good Models. - Cynthia Rudin; Chudi Zhong; Lesia Semenova; Margo I. Seltzer; Ronald Parr; Jiachang Liu 001; Srikar Katta; Jon Donnelly; Harry Chen; Zachery Boner (CoRR, 2024)

This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN. - Dennis Tang; Jon Donnelly; Alina Jade Barnett; Lesia Semenova; Jin Jing; Peter Hadar; Ioannis Karakis; Olga Selioutski; Kehan Zhao; M. Brandon Westover; Cynthia Rudin (MICCAI (14), 2025)

Fast and interpretable mortality risk scores for critical care patients. - Chloe Qinyu Zhu; Muhang Tian; Lesia Semenova; Jiachang Liu 001; Jack Xu; Joseph Scarpa; Cynthia Rudin (J. Am. Medical Informatics Assoc., 2025)