Improving Gradient Regularization using Complex-Valued Neural Networks. - Eric C. Yeats; Yiran Chen 001; Hai Li 001 (ICML, 2021)

CMOS Implementation of Spiking Equilibrium Propagation for Real-Time Learning. - Brady Taylor; Nicky Ramos; Eric C. Yeats; Hai Li 001 (AICAS, 2022)

NashAE: Disentangling Representations Through Adversarial Covariance Minimization. - Eric C. Yeats; Frank Liu 001; David Womble; Hai Helen Li (ECCV (27), 2022)

Disentangling Learning Representations with Density Estimation. - Eric C. Yeats; Frank Y. Liu; Hai Helen Li (ICLR, 2023)

Adversarial Estimation of Topological Dimension with Harmonic Score Maps. - Eric C. Yeats; Cameron Darwin; Frank Liu 001; Hai Li 001 (CoRR, 2023)

MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier. - Bokyung Kim; Qijia Huang; Brady Taylor; Qilin Zheng; Jonathan Ku; Nicky Ramos; Eric C. Yeats; Yiran Chen 001; Hai Helen Li (BioCAS, 2024)

Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models. - Jingyang Zhang; Jingwei Sun 002; Eric C. Yeats; Yang Ouyang; Martin Kuo; Jianyi Zhang; Hao Yang 018; Hai Helen Li (CoRR, 2024)

Do Counterfactual Examples Complicate Adversarial Training? - Eric C. Yeats; Cameron Darwin; Eduardo Ortega; Frank Liu 001; Hai Li 001 (CoRR, 2024)

Min-K%++: Improved Baseline for Pre-Training Data Detection from Large Language Models. - Jingyang Zhang; Jingwei Sun 002; Eric C. Yeats; Yang Ouyang; Martin Kuo; Jianyi Zhang; Hao (Frank) Yang; Hai Li 001 (ICLR, 2025)