Science

Researchers have developed a system that continuously adapts to changing online conversations, allowing it to forecast emerging trends in real-time.

A new deep learning approach successfully separates turbulent flows from underlying background currents in complex hydrodynamic simulations.

New research demonstrates that cutting-edge deep research agents can be effectively trained offline, challenging the conventional reliance on costly and complex online reinforcement learning.

A new approach generates synthetic examples to understand why deep learning models make decisions on graph data, offering a global view into their reasoning.

New research reveals that artificial intelligence agents can learn to coordinate pricing strategies in competitive markets, potentially leading to inflated prices and reduced consumer welfare.

Researchers have developed a reinforcement learning system that intelligently navigates closing auctions, outperforming conventional market-making strategies.

A new generative model leverages artificial intelligence to create realistic financial data, improving the performance of portfolio optimization strategies.

A new framework combines generative AI and robust reinforcement learning to deliver more profitable and resilient financial trading strategies in unpredictable economic climates.

Researchers have developed a single autoregressive model capable of seamlessly generating text, images, and speech, moving beyond modality-specific architectures.

New research reveals that carefully crafted self-supervised learning techniques can unlock more sensitive brain imaging biomarkers for earlier and more accurate Alzheimer’s disease diagnosis.