Alternatives and similar repositories for working-women:

Users that are interested in working-women are comparing it to the libraries listed below

• melifluos / Hyperbolic-Embedding
  Learning neural network embeddings in hyperbolic spaces
  ☆14Updated 5 years ago
• CharlotteMagister / GCExplainer
  ☆18Updated last year
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 6 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• clarafy / conformal-for-design
  ☆30Updated 2 years ago
• nikikilbertus / fairensics
  A python library to discover and mitigate biases in machine learning models and datasets
  ☆19Updated last year
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆26Updated 2 years ago
• guanghelee / iclr20-locally-constant-nets
  "Oblique Decision Trees from Derivatives of ReLU Networks" (ICLR 2020, previously called "Locally Constant Networks")
  ☆22Updated 3 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• satwik77 / libnmf
  Optimization and Regularization variants of Non-negative Matrix Factorization (NMF)
  ☆33Updated 6 years ago
• BorgwardtLab / WTK
  A Wasserstein Subsequence Kernel for Time Series.
  ☆21Updated 9 months ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆61Updated 3 years ago
• jacobdeasy / geometric-js
  ☆16Updated 3 years ago
• cscarv / riemannian-metric-learning-ot
  ☆17Updated last year
• moonfolk / Multilevel-Wasserstein-Means
  ☆22Updated 2 years ago
• gevaertlab / DAPL
  Autoencoder network for imputing missing values
  ☆27Updated 5 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• nkeriven / random-graph-gnn
  ☆12Updated 3 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆34Updated 4 years ago
• macwiatrak / GeneBac
  GeneBac: a modular framework for predicting antibiotic resistance from DNA sequence.
  ☆11Updated last year
• yaringal / CLGP
  Categorical Latent Gaussian Process
  ☆16Updated 10 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• ivaleraM / GLFM
  General Latent Feature Modeling for Heterogeneous data
  ☆48Updated last year
• pakdaman / calibration
  Binary Classifier Calibration Models
  ☆15Updated 8 years ago
• horacepan / MLGkernel
  Implementation of the Multiscale Laplacian Graph Kernel
  ☆18Updated 5 years ago
• leichen2018 / Ring-GNN
  ☆12Updated 4 years ago
• Pacmed / ehr_ood_detection
  Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.
  ☆21Updated 3 years ago
• davidhallac / NetworkLasso
  ☆22Updated 9 years ago
• c-hofer / tda-toolkit
  My persistent homology related code.
  ☆26Updated 5 years ago
• sssohrab / rho_VAE
  rho_VAE: an autoregressive parametrization of the VAE encoder
  ☆15Updated 5 years ago