Science

A new artificial intelligence framework is unlocking centuries of hidden climate data from historical Chinese records, providing an unprecedented look at past weather patterns.

A new approach reveals how pre-trained models already possess the knowledge needed to detect image forgeries, minimizing the need for extensive retraining.

A new study rigorously benchmarks the performance of several generative machine learning approaches in solving inverse design challenges, particularly within the demanding field of gas turbine combustor design.

Researchers have developed a system using AI agents to automatically generate and resolve forecasting questions, tackling a critical bottleneck in evaluating predictive AI models.

A new approach leverages network analysis and machine learning to identify malicious automated traffic in e-commerce without impacting legitimate users.

A new approach to autonomous racing focuses on directly incorporating track-specific vehicle dynamics into trajectory optimization, achieving faster lap times through iterative learning.

A new approach to network pruning dynamically creates specialized subnetworks to better handle the complexities of heterogeneous data.

A new neural network framework is pushing the boundaries of optimization, delivering improved solutions for notoriously difficult routing problems.

Researchers have developed a novel method to address security and fairness concerns in transformer models by subtly altering attention patterns during operation.

Researchers have developed a novel framework, NetMamba+, that harnesses the power of the Mamba architecture to dramatically improve the speed and accuracy of identifying network traffic types.