Alternatives and similar repositories for FastApproximateQAP

Users that are interested in FastApproximateQAP are comparing it to the libraries listed below

• gn-exp / gn-exp
  Anonymous Repository for ICML LRG Workshop: On Explainability Techniques for Graph Convolutional Networks
  ☆23Updated 6 years ago
• hexiangnan / CoNMF
  Co-regularized Non-negative Matrix Factorization
  ☆18Updated 8 years ago
• danielegrattarola / cdt-ccm-aae
  Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds (2018, https://arxiv.org/abs/1805.06299)
  ☆11Updated 5 years ago
• aditya-grover / uae
  Uncertainty Autoencoders, AISTATS 2019
  ☆56Updated 6 years ago
• miskcoo / kscore
  Nonparametric Score Estimators, ICML 2020
  ☆36Updated 4 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• sharonFogel / CPAC
  Pytorch implementation of our article "Clustering-driven Deep Embedding with Pairwise Constraints"
  ☆27Updated 7 years ago
• xbresson / spatial_graph_convnets
  PyTorch implementation of residual gated graph ConvNets, ICLR’18
  ☆124Updated 6 years ago
• nrkarthikeyan / topology-decision-boundaries
  Topology of decision boundaries
  ☆28Updated 6 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆104Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• fangchangma / invert-generative-networks
  NIPS 2018 "Invertibility of Convolutional Generative Networks from Partial Measurements"
  ☆20Updated 6 years ago
• giannisnik / cnn-graph-classification
  A convolutional neural network for graph classification in PyTorch
  ☆91Updated 6 years ago
• cnmusco / graph-similarity-learning
  Algorithms for learning network structure from effective resistances and other random-walk-based similarities.
  ☆31Updated 7 years ago
• rusty1s / embedded_gcnn
  Embedded Graph Convolutional Neural Networks (EGCNN) in TensorFlow
  ☆77Updated 7 years ago
• wilson-ye-chen / sp-mcmc
  MATLAB code for Stein Point Markov Chain Monte Carlo.
  ☆13Updated 6 years ago
• greentfrapp / doping
  Code for DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
  ☆15Updated 7 years ago
• erichson / rTensor
  Randomized Tensor Decompositions
  ☆30Updated 9 years ago
• malllabiisc / ConfGCN
  AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
  ☆59Updated 6 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆23Updated 6 years ago
• nimadehmamy / Understanding-GCN
  code for the paper in NeurIPS 2019
  ☆40Updated 2 years ago
• akashgit / VEEGAN
  VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
  ☆40Updated 6 years ago
• JiaxuanYou / G2SAT
  G2SAT: Learning to Generate SAT Formulas
  ☆49Updated 5 years ago
• mitmul / chainer-nri
  Reproduction work of "Neural Relational Inference for Interacting Systems" in Chainer
  ☆34Updated 6 years ago
• jnhujnhu / VR-SGD
  A demo for VR-SGD(Comparing to some state-of-the-art algorithms).
  ☆13Updated 7 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆20Updated 6 years ago
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆45Updated 6 years ago
• muhanzhang / D-VAE
  D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019
  ☆142Updated 5 years ago
• zhenxuan00 / graphical-gan
  source code of the paper Graphical Generative Adversarial Networks
  ☆71Updated 6 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago