Alternatives and similar repositories for edge-weighted-online-bipartite-matching

Users that are interested in edge-weighted-online-bipartite-matching are comparing it to the libraries listed below

• bwilder0 / clusternet
  Code release for NeurIPS 2019 paper "End to End Learning and Optimization on Graphs"
  ☆90Updated 5 years ago
• 000Justin000 / ssl_edge
  Code for "Graph-based Semi-Supervised & Active Learning for Edge Flows"
  ☆15Updated 6 years ago
• isl-org / NPHard
  Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
  ☆154Updated 10 months ago
• idea-iitd / GCOMB
  ☆35Updated 2 years ago
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated last year
• NNReasoning / What-Can-Neural-Networks-Reason-About
  ☆44Updated 5 years ago
• hongyuanmei / nce-mpp
  Source code for Noise-Contrastive Estimation for Multivariate Point Processes (NeurIPS 2020).
  ☆15Updated 4 years ago
• aurelienbibaut / DQN_MVC
  Implementation of Learning Combinatorial Optimization Algorithms over Graphs, by Hanjun Dai et al. (2017)
  ☆33Updated 7 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• meowoodie / Learning-Temporal-Point-Processes-via-Reinforcement-Learning
  PPG (Point Process Generator) is a Reinforcement Learning framework that is able to produce actions by imitating expert sequences.
  ☆15Updated 6 years ago
• matenure / OTCoarsening
  Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport
  ☆37Updated 4 years ago
• LingxiaoShawn / PairNorm
  Source code for PairNorm (ICLR 2020)
  ☆78Updated 5 years ago
• balcilar / Spectral-Designed-Graph-Convolutions
  Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper
  ☆50Updated 4 years ago
• yifan-h / CS-GNN
  Measuring and Improving the Use of Graph Information in Graph Neural Networks
  ☆83Updated 11 months ago
• louisv123 / COLGE
  ☆37Updated 6 years ago
• LARS-research / DiffMG
  [KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
  ☆30Updated 4 years ago
• uoguelph-mlrg / LDG
  PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"
  ☆103Updated 4 years ago
• geopanag / DiffuGreedy-Influence-Maximization
  ☆31Updated 3 years ago
• afansi / multiscalegnn
  Implementation of the paper "Community Detection with Graph Neural Networks", [1] in Pytorch
  ☆37Updated 7 years ago
• Stalence / erdos_neu
  Official Repo for the NeurIPS2020 paper "Erdos Goes Neural: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs"
  ☆49Updated 3 years ago
• zhengdao-chen / GNN4CD
  Supervised community detection with line graph neural networks
  ☆89Updated 4 years ago
• Hanjun-Dai / steady_state_embedding
  Learning Steady-States of Iterative Algorithms over Graphs
  ☆40Updated 6 years ago
• StatsDLMathsRecomSys / Self-attention-with-Functional-Time-Representation-Learning
  ☆50Updated 2 years ago
• huawei-noah / BGCN
  A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
  ☆161Updated 5 years ago
• facebookresearch / neural-rewriter
  Learning to Perform Local Rewriting for Combinatorial Optimization
  ☆151Updated 5 years ago
• xbresson / spatial_graph_convnets
  PyTorch implementation of residual gated graph ConvNets, ICLR’18
  ☆122Updated 6 years ago
• amirkhas / GraphMemoryNet
  Memory-Based Graph Networks
  ☆103Updated 3 years ago
• shuowang-ai / GeniePath-pytorch
  This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxi…
  ☆104Updated 11 months ago
• karl-zhao / benchmarking-gnns-pyg
  ☆31Updated 2 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆43Updated 6 years ago