Latest Articles for Computational Science

Explore key concepts of Grassmann, flag, and Stiefel manifolds and their applications.

CGRL tackles challenges in GNNs, improving classification despite popularity bias and noise.

Research introduces a self-interaction potential to enhance Density Functional Theory predictions.

Learn how deep backward dynamic programming addresses nonlinear partial differential equations.

An overview of the complexities in modeling neutron star merger events.

Introducing PSNE, a method to improve network embeddings efficiently and effectively.

Machine learning speeds up potential energy surface calculations for molecules like ethanol.

Research shows enhanced performance in language models using adaptive test-time computation.

A look at high-order numerical methods for fluid dynamics.

A new method improves predictions of protein functions using advanced techniques.

AI is streamlining the process of creating quantum circuits through better synthesis methods.

A novel approach for clustering molecular dynamics data to improve drug design.

A new method improves solutions to complex elliptic PDEs in engineering and science.

Innovative approach connects N-body simulations to accurate galaxy counts efficiently.

Heavy-ion collisions provide insights into the Quark-Gluon Plasma and nuclear matter.

A new approach to enhance accuracy in hyperbolic conservation laws using jump filters.

This article presents a new method for simulating quantum systems with changing forces.

This article discusses enhancing VPINNs efficiency using Least Squares and gradient descent.

MAPred combines sequence and structure data for better enzyme function predictions.

Exploring how RL improves diffusion models for targeted outcomes.

Research reveals how energy moves in quantum systems using advanced simulations.

New methods improve photon loss management in quantum computing.

A look into the Extended Generator Coordinate Method in nuclear physics.

HiFuse enhances the speed and efficiency of heterogeneous graph neural networks.

A new method for resource estimation in quantum computing circuits.

A new heuristic enhances solution finding in MILP problems.

A new tool improves the modeling of gamma-ray behavior in the universe.

Recent advancements in studying warm dense matter using Bohm SPH show promising results.

cuVegas enhances numerical integration efficiency using GPU technology for complex tasks.

This paper discusses the role of bath correlation functions in open quantum systems.

Explore how random time steps improve solutions to ordinary differential equations.

New activation functions improve neural networks for solving complex equations.

An overview of space-time multigrid methods and their applications in various fields.

A look into how recurrent flows help analyze turbulence.

New methods improve understanding of particle and energy movement in complex systems.

Discover how protein language models aid in predicting protein behaviors and functions.

A new model, XPaiNN, enhances predictions in quantum chemistry using machine learning approaches.

New techniques improve efficiency in sampling and energy calculations for quantum chemistry.

Persistent sampling enhances efficiency in Sequential Monte Carlo methods for data analysis.

mBLOR functional enhances Density Functional Theory for better material predictions.