What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, ...

Artificial intelligence and machine learning are transforming acute respiratory distress syndrome (ARDS) management, enabling ...

Upwork reports growing demand for AI, data science, finance, consulting, coding, customer service, and creative roles by 2025 ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

In this paper, we propose a brain modularity-constrained dynamic representation learning framework for interpretable fMRI analysis, consisting of dynamic graph construction, dynamic graph learning via ...

We present a high-throughput, end-to-end pipeline for organic crystal structure prediction (CSP)─the problem of identifying the stable crystal structures that will form from a given molecule based ...

A collection of important graph embedding, classification and representation learning papers with implementations.

As machine learning algorithms are increasingly deployed for high-impact automated decision-making, the presence of bias (in datasets or tasks) gradually becomes one of the most critical challenges in ...