Python-based framework makes climate dynamics more approachable for students and researchers

A team of researchers at the University of Miami has developed a global atmospheric modeling framework that blends powerful ...
IEEE

Reinforcement Learning for Solving Colored Traveling Salesman Problems: An Entropy-Insensitive Attention Approach

Abstract: The utilization of neural network models for solving combinatorial optimization problems (COPs) has gained significant attention in recent years and has demonstrated encouraging outcomes in ...
Frontiers

Optimal portfolio selection in jump-uncertain stochastic markets via maximum principle and dynamic programming

1 Department of Statistics and Mathematics, Bindura University of Science Education, Bindura, Zimbabwe 2 Department of Mathematics, University of Botswana, Gaborone, Botswana This study develops a ...
IEEE

Performance Evaluation of Heuristic and Meta-Heuristic Algorithms on Large-Scale Travelling Salesman Problem Instances

Abstract: The Travelling Salesman Problem (TSP) is a well known method for the optimisation problem that asks you to find the shortest route that visits each city in a set exactly once and then goes ...
GitHub

SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

To prevent initialization failure of control points, you use the argument --init_isotropic_gs_with_all_colmap_pcl on self-captured datasets. To begin the training, select the 'start' button. The ...
GitHub

MCP server to run Python code in a sandbox.

Code is executed using Pyodide in Deno and is therefore isolated from the rest of the operating system. Under the hood, code_sandbox runs an MCP server using stdio. You can run multiple code blocks ...