Google claims its latest quantum algorithm can outperform supercomputers on a real-world task

Researchers from Google Quantum AI report that their quantum processor, Willow, ran an algorithm for a quantum computer that ...
IEEE

Deep Reinforcement Learning Algorithm Based on Graph Weight Multi-Pointer Network for Solving Multiobjective Traveling Salesman Problem

Abstract: The multiobjective traveling salesman problem (MOTSP) is a class of classical multiobjective combinatorial optimization problems (MOCOPs), attracting significant interest across various ...
Frontiers

GTAT-GRN: a graph topology-aware attention method with multi-source feature fusion for gene regulatory network inference

Gene regulatory network (GRN) inference is a central task in systems biology. However, due to the noisy nature of gene expression data and the diversity of regulatory structures, accurate GRN ...
Phys.org

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 ...
Geeky Gadgets

Claude 4.5 Sonnet Fully Tested : From Coding to Complex Problem Solving

What if an AI could not only write code but also reason through complex problems, manage multi-step workflows for hours, and even design a functional game or simulate a solar system? Enter Claude ...
IEEE

Efficient and Robust Graph Coloring Algorithm for Graph Coloring Problem: Malatya Vertex Coloring Algorithm

Abstract: The graph coloring problem involves coloring the nodes of a graph using the minimum number of colors such that no two adjacent nodes share the same color. This NP-hard problem has various ...