Latest Articles for Scientific Computing

Learn how PINNs combine machine learning and physics to solve complex problems.

Learn how Python aids in minimizing energy in complex systems.

Exploring PETScML's impact on scientific machine learning through second-order methods.

Efficiently managing large data through low-rank tensor-train approximation techniques.

An overview of finite-volume schemes and their applications in numerical analysis.

Exploring the role of randomized algorithms in simplifying complex data.

CViT merges operator learning with conditioned neural fields for improved scientific modeling.

Discussing methods to improve data management in training large AI models.

GPU methods enhance adaptive finite element computations, improving speed and efficiency.

A new method enhances training for neural networks solving partial differential equations.

A new method boosts matrix multiplication performance using sparse matrices.

Discover how machine learning is tackling complex partial differential equations.

A novel approach uses transformers to enhance PDE solving efficiency and flexibility.

New techniques for fast kernel matrix approximations using Chebyshev and tensor train methods.

This article discusses the importance of learning operators in Banach spaces for scientific computing.

This method enhances understanding of model behavior through input-output relationships.

Learn how TCI breaks down large data for easier analysis.

This article examines the application of neural networks in solving diffusion-reaction equations.

DASTAC enhances tensor computations by combining dense and sparse techniques for efficiency.

This article reviews matvec's efficiency in single and multiple GPU environments.

Exploring improved learning rates in neural networks for scientific computing.

CausalRegNet enhances causal structure learning through realistic data generation.

New methods improve training and performance of Physics-Informed Kolmogorov-Arnold Networks.

Using FPGAs and HLS tools to enhance FTLE calculations in fluid dynamics.

A new method using ray tracing for efficient particle interaction in 3D spaces.

A new framework enhances neural network processing for scientific research.

PINNs merge physics with data to solve complex scientific problems efficiently.

A new method improves model accuracy in statistical analysis.

This article examines how Coarray and CUDA Fortran integration enhances computing performance.

A new method enhances the quality of tetrahedral meshes in 3D modeling.

A novel compressor boosts GMRES performance in solving linear equations.

Lowering calculation precision without losing accuracy using R2F2 technology.

QHyper simplifies the use of quantum computing for combinatorial optimization tasks.

A new method enhances the efficiency of charged particle simulations.

Botfip-LLM combines diverse data to enhance understanding in scientific computing.

Learn how to handle the complexities of indefinite matrices with effective strategies.

Neural operators offer new solutions for complex partial differential equations in science and engineering.

Discover how quadrature rules and splines work together in numerical analysis.

Learn how neural operators transform scientific computing and solve complex problems.

A look into how Effective Field Theory simplifies particle interactions.