AI techniques excel at solving complex equations in physics, especially inverse problems

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...
Developer Tech

GitLab launches custom AI agents and Knowledge Graph

GitLab's latest release uses AI for more than just making code completion smarter, with customisable agents, a Knowledge ...
IEEE

Inverse Optimal Control for Multiphase Cost Functions

Abstract: In this paper, we consider a dynamical system whose trajectory is a result of minimizing a multiphase cost function. The multiphase cost function is assumed to be a weighted sum of specified ...
IEEE

Analyzing the Suitability of Cost Functions for Explaining and Imitating Human Driving Behavior based on Inverse Reinforcement Learning

Abstract: Autonomous vehicles are sharing the road with human drivers. In order to facilitate interactive driving and cooperative behavior in dense traffic, a thorough understanding and representation ...
GitHub

Learning Regularization for Graph Inverse Problems (GRIPs)

This repository contains the source code for our AAAI-2025 paper. Comments have been incorporated into the python scripts to help with clarity. In recent years, Graph Neural Networks (GNNs) have been ...
GitHub

Inverse Reinforcement Learning with Diffusion Models

Code for the thesis "Inverse Reinforcement Learning (IRL) with Diffusion Models". This repository contains the implementation of diffusion models for solving IRL tasks by learning reward functions ...