Aaron J. Havens

According to our database, Aaron J. Havens authored at least 15 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

CoRR, 2024

Fine-grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention.

Aaron J. Havens, Alexandre Araujo, Huan Zhang, Bin Hu

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

IEEE Control. Syst. Lett., 2023

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models.

Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Algebraic Perspective on Lipschitz Neural Networks.

Alexandre Araujo, Aaron J. Havens, Blaise Delattre, Alexandre Allauzen, Bin Hu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Revisiting PGD Attacks for Stability Analysis of Large-Scale Nonlinear Systems and Perception-Based Control.

Aaron J. Havens, Darioush Keivan, Peter Seiler, Geir E. Dullerud, Bin Hu

CoRR, 2022

Model-Free μ Synthesis via Adversarial Reinforcement Learning.

Darioush Keivan, Aaron J. Havens, Peter Seiler, Geir E. Dullerud, Bin Hu

Proceedings of the American Control Conference, 2022

2021

Forced Variational Integrator Networks for Prediction and Control of Mechanical Systems.

Aaron J. Havens, Girish Chowdhary

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

On Imitation Learning of Linear Control Policies: Enforcing Stability and Robustness Constraints via LMI Conditions.

Aaron J. Havens, Bin Hu

Proceedings of the 2021 American Control Conference, 2021

2020

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, Girish Krishnan

Proceedings of the Robotics: Science and Systems XVI, 2020

2019

Learning Latent State Spaces for Planning through Reward Prediction.

Aaron J. Havens, Yi Ouyang, Prabhat Nagarajan, Yasuhiro Fujita

CoRR, 2019

Learning to Cope with Adversarial Attacks.

Xian Yeow Lee, Aaron J. Havens, Girish Chowdhary, Soumik Sarkar

CoRR, 2019

2018

Online Robust Policy Learning in the Presence of Unknown Adversaries.

Aaron J. Havens, Zhanhong Jiang, Soumik Sarkar

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018