Papers with Code 아카이브

Graph Property Prediction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

7

평가표

5

보존된 평가 기록

128

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/akshaysubr/TEGAN

Generative Adversarial Networks

https://github.com/alectryonexamples/gan_tf2

Generative Adversarial Networks

https://github.com/alephzr/ie-gan

Generative Adversarial Networks

https://github.com/alexOarga/haiku-geometric

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/alexOarga/haiku-geometric/blob/main/haiku_geometric/nn/conv/gin_conv.py

How Powerful are Graph Neural Networks?

https://github.com/alexOarga/haiku-geometric/blob/main/haiku_geometric/nn/conv/pna_conv.py

Principal Neighbourhood Aggregation for Graph Nets

https://github.com/alililia/ms_contrib/tree/main/ascend_gcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/alililia/ms_contrib/tree/main/gpu_gcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/alles9fresser/Vanilla-GAN

Generative Adversarial Networks

https://github.com/allnightlight/ConditionalWassersteinAutoencoderPoweredBySinkhornDistance

Generative Adversarial Networks

https://github.com/animesh-007/Basic_GAN_Implementation

Generative Adversarial Networks

https://github.com/anish-lu-yihe/SVRT-by-GAT

Graph Attention Networks

https://github.com/arangoml/fastgraphml

Graph Attention Networks

https://github.com/arnonbruno/ganify

Generative Adversarial Networks

https://github.com/arpit2412/Generative-Adversarial-Network-/tree/master/GAN/MNIST_GAN/MNIST%20Easy

Generative Adversarial Networks

https://github.com/asarigun/GraphMixerNetworks

Principal Neighbourhood Aggregation for Graph Nets

https://github.com/ashantanu/DCGAN

Generative Adversarial Networks

https://github.com/ashishmurali/Generative-Adversarial-Network

Generative Adversarial Networks

https://github.com/ashukid/Conditional-GAN-pytorch

Generative Adversarial Networks

https://github.com/asif-salim/GCN-Graph_Convolutional_Network

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/asiltureli/gan-in-colab

Generative Adversarial Networks

https://github.com/atomicarchitects/dens

Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

https://github.com/avillemin/GANs

Generative Adversarial Networks

https://github.com/bardank/dc-gan

Generative Adversarial Networks

https://github.com/basile-bron/Artificial-Intelligence-Bible

Generative Adversarial Networks

https://github.com/basile-bron/Artificial-Intelligence-Lexical

Generative Adversarial Networks

https://github.com/basiralab/RG-Select

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/basiralab/Reproducible-Generative-Learning

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/basiralab/reproduciblefedgnn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/bcsrn/gcn

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/bepping/non-oversmoothing-gcns

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/beresandras/gan-flavours-keras

Generative Adversarial Networks

https://github.com/blueberryc/pyGAT

Graph Attention Networks

https://github.com/borgwardtlab/pst

Structure-Aware Transformer for Graph Representation Learning

https://github.com/bourcierj/rdfia-tme10-gan

Generative Adversarial Networks

https://github.com/bowu/GraphSearch

Graph Attention Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.