research
∙
06/10/2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations
We present a framework and algorithms to learn controlled dynamics model...
share
research
∙
06/10/2023
Autonomous Drifting with 3 Minutes of Data via Learned Tire Models
Near the limits of adhesion, the forces generated by a tire are nonlinea...
research
∙
01/09/2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
Data-driven control algorithms use observations of system dynamics to co...
research
∙
12/30/2022
Task-Guided IRL in POMDPs that Scales
In inverse reinforcement learning (IRL), a learning agent infers a rewar...
research
∙
01/14/2022
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs
Neural ordinary differential equations (NODEs) – parametrizations of dif...
research
∙
09/14/2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
Effective inclusion of physics-based knowledge into deep neural network ...
research
∙
06/29/2021
Probabilistic Control of Heterogeneous Swarms Subject to Graph Temporal Logic Specifications: A Decentralized and Scalable Approach
We develop a probabilistic control algorithm, , for swarms of agents wit...
research
∙
06/19/2021
Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information
We develop a learning-based control algorithm for unknown dynamical syst...
research
∙
05/28/2021