Alternatives and similar repositories for ntds_2019

Users that are interested in ntds_2019 are comparing it to the libraries listed below

• mdeff / ntds_2018
  Material for the EPFL master course "A Network Tour of Data Science", edition 2018.
  ☆58Updated 5 years ago
• scottgigante / m-phate
  Multislice PHATE for tensor embeddings
  ☆60Updated 4 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆129Updated 5 years ago
• aGIToz / Graph_Signal_Processing
  Signal processing on graphs using torch_geometric.
  ☆14Updated 3 years ago
• xbresson / CE9010_2018
  Python notebooks and slides for CE9010: Introduction to Data Science, Semester 2 2017/18
  ☆52Updated 6 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• ritchieng / eigenvectors-from-eigenvalues
  PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.
  ☆98Updated 3 years ago
• epfml / opt-shortcourse
  Short Course on Optimization for Machine Learning - Slides and Practical Lab - Pre-doc Summer School on Learning Systems, July 3 to 7, 20…
  ☆18Updated 7 years ago
• mdeff / ntds_2017
  Material for the EPFL master course "A Network Tour of Data Science", edition 2017.
  ☆66Updated 5 years ago
• JeanKossaifi / ifi-summer-school
  Slides and notebooks for the IfI Summer School 2018 on Machine Learning
  ☆36Updated 7 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 years ago
• epfl-ada-2018 / ADA2018-Tutorials
  Repo for tutorials
  ☆13Updated 6 years ago
• crisbodnar / dgm
  Deep Graph Mapper: Seeing Graphs through the Neural Lens
  ☆58Updated 2 years ago
• dglai / dgl_winter_school
  ☆32Updated 4 years ago
• timsainb / ParametricUMAP_paper
  Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep…
  ☆151Updated 4 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• mdeff / pygsp_tutorial_graphsip
  Graph signal processing tutorial, presented at the GraphSiP summer school.
  ☆76Updated 6 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 5 years ago
• paulmorio / geo2dr
  Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.
  ☆46Updated 2 years ago
• rflamary / OTML_Statlearn2018
  Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018
  ☆26Updated 7 years ago
• drewwilimitis / hyperbolic-learning
  Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
  ☆137Updated 5 years ago
• mlss-skoltech / tutorials
  repository with the tutorials for MLSS Skoltech
  ☆66Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• fehiepsi / rethinking-pyro
  Statistical Rethinking with PyTorch and Pyro
  ☆164Updated 3 months ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• mlss-2019 / tutorials
  ☆275Updated 5 years ago
• leopd / geometric-intuition
  Understanding ML and deep learning through geometry
  ☆157Updated 3 years ago
• xbresson / CE7454_2018
  Deep learning course CE7454, 2018
  ☆79Updated 5 years ago
• jkbren / einet
  Uncertainty and causal emergence in complex networks
  ☆118Updated 3 years ago
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 5 years ago