InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate 事件

InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate arXiv:2606.00241v1 Announce Type: cross Abstract: Measuring statistical dependency between high-dimensional random variables is a fundamental task in data science and machine learning. Neural mutual information (MI) estimators offer a promising avenue, but they typically require costly iterative optimization for each new dataset, making them impractical for real-time applications. We present InfoAtlas, a foundation mode