Alternatives and similar repositories for topological-autoencoders

Users that are interested in topological-autoencoders are comparing it to the libraries listed below

• c-hofer / torchph
  The essence of my research, distilled for reusability. Enjoy 🥃!
  ☆69Updated last year
• MathieuCarriere / perslay
  Implementation of the PersLay layer for persistence diagrams
  ☆84Updated 2 years ago
• aidos-lab / pytorch-topological
  A topological machine learning framework based on PyTorch
  ☆189Updated 3 months ago
• BorgwardtLab / TOGL
  Topological Graph Neural Networks (ICLR 2022)
  ☆122Updated 3 years ago
• geomstats / challenge-iclr-2022
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆52Updated 3 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆102Updated 2 years ago
• simonzhang00 / ripser-plusplus
  Ripser++: GPU-accelerated computation of Vietoris–Rips persistence barcodes
  ☆113Updated 2 years ago
• Pseudomanifold / pyper
  Python-based persistent homology algorithms
  ☆19Updated 2 years ago
• danchern97 / RTD_AE
  This is an official repository for "Learning topology-preserving data representations" presented at ICLR 2023 conference.
  ☆33Updated 2 years ago
• c-hofer / jmlr_2019
  Code for JMLR paper ``Learning Representations of Persistence Barcodes``
  ☆24Updated 5 years ago
• CSU-TDA / PersistenceImages
  This code accompanies the paper "Persistence Images: A Stable Vector Representation of Persistent Homology".
  ☆43Updated 4 years ago
• scikit-learn-contrib / scikit-dimension
  A Python package for intrinsic dimension estimation
  ☆93Updated 3 weeks ago
• MathieuCarriere / difftda
  Persistence differentiation with Gudhi and Tensorflow
  ☆19Updated 2 years ago
• KevinMoonLab / GRAE
  Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
  ☆24Updated last year
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• topnn / topnn_framework
  ☆35Updated 4 years ago
• trneedham / gromov-wasserstein-statistics
  Statistics on the space of asymmetric networks via Gromov-Wasserstein distance
  ☆13Updated 5 years ago
• scikit-tda / persim
  Distances and representations of persistence diagrams
  ☆131Updated 2 weeks ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• scikit-tda / pervect
  Vectorization of persistence diagrams and approximate Wasserstein distance
  ☆27Updated 5 years ago
• scikit-tda / tadasets
  Synthetic data sets apt for Topological Data Analysis
  ☆36Updated last week
• KrishnaswamyLab / DiffusionEMD
  Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings
  ☆38Updated 10 months ago
• gjkoplik / topology-demos
  explanation / demos of topology concepts
  ☆14Updated 3 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• HazyResearch / HoroPCA
  Hyperbolic PCA via Horospherical Projections
  ☆73Updated 2 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…
  ☆79Updated 4 years ago
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆53Updated 8 months ago
• drewwilimitis / hyperbolic-learning
  Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
  ☆140Updated 5 years ago
• giotto-ai / giotto-deep
  Deep learning made topological.
  ☆86Updated last year
• BorgwardtLab / fMRI_Cubical_Persistence
  Code of our NeurIPS 2020 publication 'Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence'
  ☆25Updated 4 years ago