From superconductors and AI-driven quantum analysis to black hole physics, Day 2 of QMAT2026 highlighted cutting-edge ...

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...

Scientists at Rice University have produced the first full, dye-free molecular atlas of an Alzheimer’s brain. By combining laser-based imaging with machine learning, they uncovered chemical changes ...

Abstract: Multitemporal landslide inventory mapping plays a vital role in postdisaster reconstruction, landslide prevention, and regional ecosystem restoration. While deep learning methods have ...

Abstract: Seismic high-resolution reconstruction is a key step in retrieving high-resolution components to characterize subsurface geological structures. Recently, deep learning (DL) has emerged as an ...

Unsupervised machine learning, combined with the analysis of earthquake sequences as interacting events, can help identify precursor signals that may occur before earthquakes. Credit: Shutterstock A ...

Tesla AI chief Ashok Elluswamy said the build is rolling out to “AI3 early-access customers” and will expand “over the next ...

We propose MaskCut approach to generate pseudo-masks for multiple objects in an image. CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K. CutLER exhibits ...

🔥 Some other prompt learning projects from our lab may interest you: Advancing Textual Prompt Learning with Anchored Attributes. Zheng Li, Yibing Song, Ming-Ming Cheng, Xiang Li#, Jian Yang#. In this ...

Get an overview of generative AI, how it works, and how it’s poised to shape the future. Generative AI refers to a class of AI models, such as the GPT series or Llama, that analyzes large amounts of ...

Sophia Learning has started blocking students from downloading the course materials and using Ctrl-F to find answers during ...