aGIToz / Graph_Signal_Processing

Related projects: ⓘ

• xbresson / IPAM_Tutorial_2019
  Notebooks for IPAM Tutorial, March 15 2019
  ☆24Updated 5 years ago
• geomstats / challenge-iclr-2022
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆50Updated 2 years ago
• geomstats / applications
  Examples of more involved applications using Geomstats
  ☆32Updated 3 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆113Updated last year
• tychovdo / lila
  Code for "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations"
  ☆23Updated last year
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆68Updated last year
• aGIToz / Pytorch_pdegraph
  Running PDEs on graph
  ☆27Updated last year
• geomstats / challenge-iclr-2021
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆51Updated 2 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆41Updated last year
• mdeff / pygsp_tutorial_graphsip
  Graph signal processing tutorial, presented at the GraphSiP summer school.
  ☆71Updated 5 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆30Updated 3 years ago
• louaaron / TopologicalDeepLearning
  A collection of Topology Methods in Deep Learning
  ☆16Updated 4 years ago
• stefaniaebli / simplicial_neural_networks
  Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…
  ☆72Updated 3 years ago
• MarcTLaw / UltrahyperbolicRepresentation
  Ultrahyperbolic Representation Learning
  ☆11Updated 4 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• scikit-tda / pervect
  Vectorization of persistence diagrams and approximate Wasserstein distance
  ☆26Updated 4 years ago
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆23Updated last year
• Pseudomanifold / pyper
  Python-based persistent homology algorithms
  ☆18Updated last year
• crisbodnar / dgm
  Deep Graph Mapper: Seeing Graphs through the Neural Lens
  ☆53Updated last year
• dimkal89 / rvae
  ☆36Updated 4 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 2 years ago
• paulmorio / geo2dr
  Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.
  ☆44Updated last year
• MathieuCarriere / perslocsig
  Local signatures for 3D shapes with persistent homology
  ☆13Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• haguettaz / ChebLieNet
  ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
  ☆15Updated last month
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆18Updated 4 years ago
• MathieuCarriere / perslay
  Implementation of the PersLay layer for persistence diagrams
  ☆79Updated 11 months ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated last year
• c-hofer / jmlr_2019
  Code for JMLR paper ``Learning Representations of Persistence Barcodes``
  ☆23Updated 4 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆21Updated last year