Latest Articles for Computer Science

Examine tensor fields and their applications using momentum ray transforms.

Exploring quantum computing methods to improve network communication and problem-solving.

Exploring the relationship between data languages and topological concepts.

An overview of quantum circuit complexity and its real-world applications.

Exploring improvements in training methods for physics-informed neural networks.

A simple guide to monomial codes and their role in data transmission.

Researchers enhance GNNs for efficient mesh-based physics modeling.

Learn about logical atomicity and safe data structures in concurrent systems.

mmodel simplifies simulation coding for scientists, improving flexibility and collaboration.

New techniques enhance data generation in complex environments.

A look into subgraph hitting in sparse and geometric intersection graphs.

Introducing cut-restriction for simpler proof analysis across logical systems.

Exploring the complexities of power series and related mathematical problems.

Multiple GFT designs enhance signal analysis in directed graphs.

A deeper look into the role of samplers in probabilistic programming.

Exploring the challenges of proving unprovable statements in logic and math.

New methods improve efficiency in program analysis using the Zones abstract domain.

Explore the properties and significance of Brownian trees in various fields.

New methods leverage quantum systems for faster string matching.

Learn about the basics and applications of graph theory across various fields.

Discover the unusual properties of exotic surfaces within four-dimensional shapes.

Examining the challenges of Boolean queries and sum-product problems.

A look into how connections form and spread in graphs.

Learn how ChatGPT generates training data to improve machine learning models.

Explore the unique properties and uses of rigidity expander graphs.

Algebraic series bridge mathematics and computer science, revealing structural relationships.

Exploring the methods for counting subgraphs in various types of graphs.

Investigating better learning methods through parameterized PAC learning.

A new method simplifies quantum circuit cutting, improving efficiency and accuracy.

A look at maximizing profit in item selection while considering costs and budget constraints.

Explore the nature and calculation of Dedekind numbers in mathematics.

Exploring how quantitative algebras apply distance measures to traditional algebraic structures.

This paper presents a new model combining transformers with CNNs for chess.

Reducing graph size improves learning efficiency in complex networks.

A look at how continuations streamline program compilation and control flow.

An overview of how pseudorandomness shapes algorithms and cryptography.

A new method enhances model training by focusing on loss landscape characteristics.

A look at the nearest neighbor problem for polygonal curves and Fréchet distance.

A new approach for efficient stochastic optimization in various fields.

Exploring how vertices in graphs can see each other without obstruction.