Data jam: introducing high school students to data science. - Saman Haqqi; Raja Sooriamurthi; Brian Macdonald; Cheryl Begandy; Judy Cameron; Berni Pirollo; Evan Becker; Jacqueline Choffo; Christopher Davis; Margaret Farrell; Jennifer Lundahl; Laura Marshall; et al. (ITiCSE, 2018)

Instability and Local Minima in GAN Training with Kernel Discriminators. - Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson K. Fletcher (NeurIPS, 2022)

Local Convergence of Gradient Descent-Ascent for Training Generative Adversarial Networks. - Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson K. Fletcher (ACSSC, 2023)

High Probability Bounds for Stochastic Continuous Submodular Maximization. - Evan Becker; Jingdong Gao; Ted Zadouri; Baharan Mirzasoleiman (AISTATS, 2023)

Cycles of Thought: Measuring LLM Confidence through Stable Explanations. - Evan Becker; Stefano Soatto (CoRR, 2024)

GAN Training With Kernel Discriminators: What Parameters Control Convergence Rates? - Evan Becker; Parthe Pandit; Sundeep Rangan; Alyson K. Fletcher (IEEE Trans. Signal Process., 2025)

Maximally-Informative Retrieval for State Space Model Generation. - Evan Becker; Benjamin Bowman; Matthew Trager; Tian Yu Liu; Luca Zancato; Wei Xia; Stefano Soatto (CoRR, 2025)