Latest Articles for Computer Science

Discover the role of QuAK in assessing system performance and safety.

New methods improve neural network performance on limited-resource devices.

Examining the challenges and significance of the Subset Sum problem in computer science.

Learn about the construction and significance of monotone arc diagrams in graph representation.

A look into memory allocation strategies and their importance in system efficiency.

Discover how Zolotarev rational functions manage values in different domains.

Explore the fundamentals of graph theory and its real-world applications.

A look into Fourier Analysis and its significance in various fields.

Learn how graphs create complex topological spaces with essential properties.

A method to ensure reliable quantum program execution with lattice surgery.

A novel algorithm improves calculations for theta functions in Schottky groups.

Researchers develop new techniques for building strong bipartite graphs.

New methods enhance efficiency in simulating complex quantum circuits.

A look into graphs, their properties, and practical applications.

Explore the complexities of scheduling tasks across multiple machines for optimal efficiency.

Analyzing the connections between Weihrauch problems and Büchi games in computer science.

A look into the BP+OTF algorithm for improving quantum computing reliability.

An overview of dynamic ASEP and its key concepts.

Exploring the significance and applications of hitting subgraphs in various fields.

A look at Adaptative Context Normalization in deep learning for image processing.

New methods inspired by nature help approximate hard problems in computing.

A framework to make neural networks' hidden insights clearer and more understandable.

This research enhances how models answer questions using tables.

Exploring a new method for tackling multi-block optimization problems effectively.

A look at how error-correcting codes ensure reliable data transmission.

Exploring how errors in catalytic computation can expand computational capabilities.

Examining dynamics of Markov processes in complex networks for diverse applications.

A new method improves accuracy in model extraction from quantum neural networks.

A new method improves the speed of spiking neural networks.

New methods enhance accuracy and consistency in language models.

Introducing an improved approach for tackling stochastic optimization problems with constraints.

A look at dimensionality reduction techniques for analyzing complex cosmological data.

An engaging assignment on DNA sequence alignment aids parallel programming education.

An overview of priority queues used in finding shortest paths in networks.

Exploring strategies for finding maximum values amid corrupted data.

Explore hyper-invariant tensor networks and their role in quantum physics simulations.

A look into the concept and applications of fibrations in mathematics.

A method for creating various maps on orientable surfaces with unique representations.

Exploring bifiltrations for improved data analysis and outlier management.

Exploring the role of high dimensional expanders in mathematics and computer science.