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 ...

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity may help explain how ...

This review examines AI and ML's role in transforming thermoelectric materials design, focusing on defect engineering and ...

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 ...