Oct 28, 2022 · Artificial Intelligence

Geometric Graph Neural Networks for Drug Discovery: 3D Structure‑Based Binding Affinity Prediction and Molecular Property Learning

This article presents a comprehensive overview of using geometric graph neural networks on the Baidu PaddleHelix platform to address challenges in drug discovery, including 3D‑structure‑aware protein‑ligand binding affinity prediction, molecular property prediction, and self‑supervised pre‑training, with experimental results showing significant improvements over existing baselines.

drug discoverygeometric-deep-learninggraph neural networks

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Geometric Graph Neural Networks for Drug Discovery: 3D Structure‑Based Binding Affinity Prediction and Molecular Property Learning

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May 10, 2022 · Artificial Intelligence

How Geometric Deep Learning Enables Spherical CNNs for Rotationally Equivariant Vision

The article explains why traditional planar CNNs fail on spherical data, describes how encoding rotational symmetry through continuous spherical representations and spherical harmonics leads to spherical convolutions that are rotation‑equivariant, and outlines the practical computation using harmonic coefficients.

Computer Visiongeometric-deep-learningrotational equivariance

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How Geometric Deep Learning Enables Spherical CNNs for Rotationally Equivariant Vision