4 papers · 1 filter
Constrained Flow Matching via Lagrangian Dual Flows
Vince Kurtz, Alexander Davydov
Flow matching is a powerful tool for generative modeling, but emerging applications in robotics, planning, and physics require inference-time constraints on generated outputs. Such…
Regularized Model Predictive Control via Contractivity and Implicit Lur'e Analysis
Ryotaro Shima, Anand Gokhale, Alexander Davydov +1
This paper develops a contraction-based stability analysis for regularized model predictive control (MPC), whose feedback law is defined implicitly by a finite-horizon optimal cont…
Learning Certified Neural Network Controllers Using Contraction and Interval Analysis
Akash Harapanahalli, Samuel Coogan, Alexander Davydov
We present a novel framework that jointly trains a neural network controller and a neural Riemannian metric with rigorous closed-loop contraction guarantees using formal bound prop…
Competition, stability, and functionality in excitatory-inhibitory neural circuits
Simone Betteti, William Retnaraj, Alexander Davydov +2
Energy-based models have become a central paradigm for understanding computation and stability in both theoretical neuroscience and machine learning. However, the energetic framewo…