"We're starting to see machine learning as a system with structure ... we just started dreaming up new methods to bring into this framework. Almost every single one we tried could be added in ...

The development of tools for reliably measuring people's empathy has thus been a key objective of many past psychology ...

The framework, Information-Contrastive Learning (I-Con), connects diverse machine learning (ML) methods, offering researchers a structured system for innovation. Developed by researchers from MIT ...

Deep-learning models analyzing MRI scans predict brain age, cognition, and amyloid pathology with high accuracy—offering a ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

Some features may also only be available in certain countries. PyTorch is a deep learning framework designed to simplify AI model development. First released by Meta AI, it was built to improve ...

The method enables faster, more cost-effective development ... Researchers at Northwestern Engineering have developed a scientific machine learning framework that predicts and inversely designs the ...

Research team used ProteinMPNN to expand the sequence space of synthetic binding proteins (SBPs), improving their solubility ...

Despite decades of research, existing methods have only been able to ... overcomes these challenges by leveraging a deep learning framework inspired by out-of-distribution (OOD) detection ...

For example, some ST methods rely on arbitrarily defined ... Japan, developed a deep-learning framework called Spatial Transcriptomics Analysis via Image-Aided Graph Contrastive Learning (STAIG).