research
∙
01/08/2022
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Electricity Demand Forecasting
Some real-world decision-making problems require making probabilistic fo...
share
research
∙
01/08/2022
Multi-Vehicle Control in Roundabouts using Decentralized Game-Theoretic Planning
Safe navigation in dense, urban driving environments remains an open pro...
research
∙
05/05/2021
Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual
Model-based paradigms for decision-making and control are becoming ubiqu...
research
∙
06/20/2020
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
System identification is a key step for model-based control, estimator d...
research
∙
04/21/2020
Structured Mechanical Models for Robot Learning and Control
Model-based methods are the dominant paradigm for controlling robotic sy...
research
∙
02/22/2019
A General Framework for Structured Learning of Mechanical Systems
Learning accurate dynamics models is necessary for optimal, compliant co...
research
∙
07/22/2018
EnsembleDAgger: A Bayesian Approach to Safe Imitation Learning
While imitation learning is often used in robotics, this approach often ...
research
∙
09/19/2017
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes
The incorporation of macro-actions (temporally extended actions) into mu...
research
∙
09/18/2017
