Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
7 个 · 按相关度排序
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
PyTorch Geometric (PyG) for graph neural networks: node/graph classification, link prediction with GCN, GAT, GraphSAGE, GIN. Message passing, mini-batches, heterogeneous graphs, neighbor sampling, explainability. Supports molecules (QM9, MoleculeNet), social/knowledge graphs, 3D point clouds. For non-graph DL use PyTorch; for classical graph algorithms use NetworkX.
中文简介正在准备中。当前显示原文说明。
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
中文简介正在准备中。当前显示原文说明。
Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system
中文简介正在准备中。当前显示原文说明。