AI models are starting to crack high-level math problems

“I was curious to establish a baseline for when LLMs are effectively able to solve open math problems compared to where they ...
Quanta Magazine

Using AI, Mathematicians Find Hidden Glitches in Fluid Equations

A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, ...
GitHub

Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance

Abstract: Recent diffusion models provide a promising zero-shot solution to noisy linear inverse problems without retraining for specific inverse problems. In this paper, we reveal that recent methods ...
IEEE

Construction of Motion Transformation Matrices Based on the D-H Parameter Method and Solving Multi-Objective Optimization Models Using Genetic Algorithms

Abstract: This paper addresses the modeling and optimization of a six-degree-of-freedom robotic arm. We establish a comprehensive mathematical model to describe its kinematic and dynamic ...
IEEE

High-Accuracy and Energy-Efficient Learning of Inverse Dynamics for High-DoF Robotic Manipulators Using Spiking Neural Networks

Abstract: Inverse dynamics maps the joint space of a robotic system to the torque space, but traditional methods for solving it rely on direct physical modeling of robots, which is difficult or even ...