Moving past speculation: How deterministic CPUs deliver predictable AI performance

As David Patterson observed in 1980, “A RISC potentially gains in speed merely from a simpler design.” Patterson’s principle of simplicity underpins a new alternative to speculation: A deterministic, ...
IEEE

Learning a Self-Supervised Low-Rank Decomposition Network for Hyperspectral Image Super-Resolution

Abstract: Hyperspectral image (HSI) super-resolution, which reconstructs a high-resolution HSI (HR-HSI) through hyperspectral and multispectral image fusion (HMIF) tasks that integrate a ...
IEEE

Fault Detection of Three-Phase Controlled Rectifiers Using Supervised Machine Learning Algorithms

Abstract: Power converters are integral to modern power systems and industrial applications, facilitating efficient and reliable energy transfer between sources and loads. However, their widespread ...
marktechpost

Stanford Researchers Released AgentFlow: In-the-Flow Reinforcement Learning RL for Modular, Tool-Using AI Agents

Flow-GRPO (Flow-based Group Refined Policy Optimization) converts long-horizon, sparse-reward optimization into tractable single-turn updates: Benchmarks. The research team evaluates four task types: ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
The University of Chicago Chronicle

New students begin their UChicago journeys

Editor's Note: Check back with this story for frequent updates throughout Orientation Week. New students of the College received a warm welcome to the University of Chicago during Opening Convocation ...