Havens, Aaron J

6 publications

ICML 2025 Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen
ICLRW 2025 Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen
ICML 2024 Fine-Grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention Aaron J Havens, Alexandre Araujo, Huan Zhang, Bin Hu
ICLR 2024 Novel Quadratic Constraints for Extending LipSDP Beyond Slope-Restricted Activations Patricia Pauli, Aaron J Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu
ICLR 2024 On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks Zi Wang, Bin Hu, Aaron J Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha
ICLR 2023 A Unified Algebraic Perspective on Lipschitz Neural Networks Alexandre Araujo, Aaron J Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu