ApproxCaliper: A Programmable Framework for Application-aware Neural Network Optimization. - Yifan Zhao 004; Hashim Sharif; Peter Pao-Huang; Vatsin Shah; Arun Narenthiran Sivakumar; Mateus Valverde Gasparino; Abdulrahman Mahmoud; Nathan Zhao; Sarita V. Adve; Girish Chowdhary 001; Sasa Misailovic; Vikram S. Adve (MLSys, 2023)

EigenFold: Generative Protein Structure Prediction with Diffusion Models. - Bowen Jing; Ezra Erives; Peter Pao-Huang; Gabriele Corso; Bonnie Berger; Tommi S. Jaakkola (CoRR, 2023)

Semi-Supervised Object Detection in the Open World. - Garvita Allabadi; Ana Lucic; Peter Pao-Huang; Yu-Xiong Wang; Vikram S. Adve (CoRR, 2023)

Geometric Generative Modeling with Noise-Conditioned Graph Networks. - Peter Pao-Huang; Mitchell Black 002; Xiaojie Qiu (CoRR, 2025)