Lists of awesome resources for geometric or topological neural network
- graph
- point cloud
- social net
- mesh
- chemistry
- depth
- TDA
- autoML
- https://github.com/deepmind/graph_nets
- https://github.com/rusty1s/pytorch_geometric
- https://github.com/facebookresearch/PyTorch-BigGraph
- https://github.com/pfnet-research/chainer-chemistry
- https://github.com/dmlc/dgl
- https://github.com/tensorflow/graphics
- https://github.com/matenure/FastGCN
- https://github.com/ethanfetaya/NRI
- https://github.com/Eilene/GWNN
- https://github.com/benedekrozemberczki/GraphWaveletNeuralNetwork
- https://github.com/tkipf/gcn
- https://github.com/charlesq34/pointnet
- https://github.com/charlesq34/pointnet2
- https://github.com/yewzijian/3DFeatNet
- https://github.com/shaohua0116/Multiview2Novelview
- https://github.com/rajammanabrolu/KG-DQN
- https://github.com/melodyguan/enas
- https://github.com/renqianluo/NAO
- https://github.com/quark0/darts
- Deep Learning on Graphs: A Survey
- Graph Neural Networks: A Review of Methods and Applications
- A Comprehensive Survey on Graph Neural Networks
- GCN
- TreeLSTM
- R-GCN
- JTNN
- LGNN
- DGMG
- Spline
- ChebConv
- NNConv
- GAT
- AGNN
- SAGE
- GIN
- ARMA
- RGCN
- Edge
- GWNN
- GraphWarpModule
- GlobalAttention
- Set2Set
- SortPool
- DenseDifferentiablePooling
- GraclusPooing
- VoxelGridPooing
- GMM
- Graph U-Net
- TopKPooing
- DeepGraphInfomax
- graph_nets
- simplfying GCN
- SfMLearner
- vid2depth
- struct2depth
- Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras
- PointNet
- PointNet++
- PointCNN
- Submanifold Sparse Convolutional Networks
- 3D Graph Embedding Learning with a Structure-aware Loss Function for Point Cloud Semantic Instance Segmentation
- Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds
- PCPNET
- VoxelNet
- Frustum PointNets for 3D Object Detection from RGB-D Data
- NAS
- PNAS
- ENAS
- EPNAS
- NAONet
- DARTS
- GHN
- A Differentiable Gaussian-like Distribution on Hyperbolic Space for Gradient-Based Learning
- Exploring Randomly Wired Neural Networks for Image Recognitio
- Beyond topological persistence: Starting from networks
- Topological Persistence in Geometry and Analysis
- PersLay
- Graph Spectral Regularization for Neural Network Interpretability
- On the Transferability of Spectral Graph Filters
- KG-DGN
- Hyperbolic Disk Embeddings for Directed Acyclic Graphs
- Graph cohomologies and rational homotopy type of configuration spaces
- Topology and curvature of metric spaces
- QM9
MoleculeNet: A Benchmark for Molecular Machine Learning Neural Message Passing for Quantum Chemistry - ModelNet[format]
- semanticscholar
- semanticscholar api
- shibuya 3d
- Stanford Large Network Dataset Collection
- neworkx
- plyfile
- rdflib
- pygsp
- pydotplus
- graphviz
- pygraphviz(require
apt install graphviz graphviz-dev)
- Vietoris-Rips complex
- prsistent homology
- barcode
- Taken's theorem
- Janko Latschev's theorem
- https://paperswithcode.com/area/graphs
- https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs
- https://ai.googleblog.com/2019/05/moving-camera-moving-people-deep.html
- https://jian-tang.com/files/AAAI19/aaai-grltutorial-part0-intro.pdf
- http://i.stanford.edu/~jure/pub/talks2/graph_gen-iclr-may19-long.pdf
- https://cs.stanford.edu/~jure/
- https://www.slideshare.net/shotarosano5/automl-in-neurips-2018
- https://medium.com/programming-soda/graph-neural-network%E3%81%AE%E5%87%A6%E7%90%86%E3%81%A8%E5%8A%B9%E6%9E%9C%E3%82%92%E7%90%86%E8%A7%A3%E3%81%99%E3%82%8B-how-powerful-are-graph-neural-networks-a26ee9245cce
- https://qiita.com/no_more_syakai/items/f1358e33e8376ae1766d
- https://www.slideshare.net/emakryo/neural-networks-for-graph-data-neurips2018pfn
- https://speakerdeck.com/m_mochizuki/ai-drug-discovery-in-the-view-of-competitions
- https://speakerdeck.com/nnchiba/point-cloud-deep-learning-survey-ver-2
- https://engineer.dena.jp/2019/06/cv-papers-19-3dvision.html