Online Robust Policy Learning in the Presence of Unknown Adversaries. - Aaron J. Havens; Zhanhong Jiang; Soumik Sarkar (NeurIPS, 2018)

Learning to Cope with Adversarial Attacks. - Xian Yeow Lee; Aaron J. Havens; Girish Chowdhary 001; Soumik Sarkar (CoRR, 2019)

Learning Latent State Spaces for Planning through Reward Prediction. - Aaron J. Havens; Yi Ouyang; Prabhat Nagarajan; Yasuhiro Fujita 001 (CoRR, 2019)

A Berry Picking Robot With A Hybrid Soft-Rigid Arm: Design and Task Space Control. - Naveen Kumar Uppalapati; Benjamin Walt; Aaron J. Havens; Armeen Mahdian; Girish Chowdhary 001; Girish Krishnan (Robotics: Science and Systems, 2020)

On Imitation Learning of Linear Control Policies: Enforcing Stability and Robustness Constraints via LMI Conditions. - Aaron J. Havens; Bin Hu 002 (ACC, 2021)

Forced Variational Integrator Networks for Prediction and Control of Mechanical Systems. - Aaron J. Havens; Girish Chowdhary 001 (L4DC, 2021)

Model-Free μ Synthesis via Adversarial Reinforcement Learning. - Darioush Keivan; Aaron J. Havens; Peter Seiler 001; Geir E. Dullerud; Bin Hu 002 (ACC, 2022)

Revisiting PGD Attacks for Stability Analysis of Large-Scale Nonlinear Systems and Perception-Based Control. - Aaron J. Havens; Darioush Keivan; Peter Seiler 001; Geir E. Dullerud; Bin Hu 002 (CoRR, 2022)

A Unified Algebraic Perspective on Lipschitz Neural Networks. - Alexandre Araujo; Aaron J. Havens; Blaise Delattre; Alexandre Allauzen; Bin Hu 002 (ICLR, 2023)

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models. - Aaron J. Havens; Alexandre Araujo; Siddharth Garg; Farshad Khorrami; Bin Hu 002 (NeurIPS, 2023)

Revisiting PGD Attacks for Stability Analysis of High-Dimensional Nonlinear Systems and Perception-Based Control. - Aaron J. Havens; Darioush Keivan; Peter J. Seiler; Geir E. Dullerud; Bin Hu 002 (IEEE Control. Syst. Lett., 2023)

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 002 (ICLR, 2024)

On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks. - Zi Wang; Bin Hu 002; Aaron J. Havens; Alexandre Araujo; Yang Zheng 001; Yudong Chen; Somesh Jha (ICLR, 2024)

Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention. - Aaron J. Havens; Alexandre Araujo; Huan Zhang; Bin Hu 002 (ICML, 2024)

Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultra. - Darioush Kevian; Usman Syed; Xingang Guo; Aaron J. Havens; Geir E. Dullerud; Peter J. Seiler; Lianhui Qin; Bin Hu 002 (CoRR, 2024)

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. - Aaron J. Havens; Benjamin Kurt Miller; Bing Yan; Carles Domingo-Enrich; Anuroop Sriram; Brandon M. Wood; Daniel Levine; Bin Hu; Brandon Amos; Brian Karrer; Xiang Fu 005; Guan-Horng Liu; et al. (CoRR, 2025)