FilippoMB / Total-variation-graph-neural-networks

Related projects ⓘ

Alternatives and complementary repositories for Total-variation-graph-neural-networks

• diningphil / continual_learning_for_graphs
  ☆13Updated 3 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• clear-nus / NCDSSM
  PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…
  ☆24Updated last year
• gravins / Anti-SymmetricDGN
  Official code repository for the papers "Anti-Symmetric DGN: a stable architecture for Deep Graph Networks" accepted at ICLR 2023; "Non-D…
  ☆10Updated 4 months ago
• DiffEqML / tutorials
  ☆10Updated 2 years ago
• lrnzgiusti / on-oversquashing
  Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)
  ☆14Updated last year
• noamrazin / gnn_interactions
  Code for reproducing experiments in "On the Ability of Graph Neural Networks to Model Interactions Between Vertices"
  ☆22Updated last year
• hadarser / SetToGraphPaper
  SetToGraph paper repository
  ☆21Updated 4 years ago
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated last year
• 000Justin000 / gnn-residual-correlation
  ☆20Updated 3 years ago
• opallab / Graph-Attention-Retrospective
  ☆11Updated 2 years ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 2 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated last year
• networkslab / rnn_flow
  ☆22Updated 3 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆30Updated 3 years ago
• samihaija / isvd
  Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning
  ☆20Updated 3 years ago
• chendiqian / IPM_MPNN
  Repo for paper: Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems, accepted at AISTATS 2024
  ☆12Updated last year
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• MingyuKim87 / NPwSA
  Official PyTorch implementation of NPwSA: "Neural Processes with Stochastic Attention: Paying more attention to the context dataset (ICLR…
  ☆10Updated 2 years ago
• thudzj / ELLA
  Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
  ☆16Updated 2 years ago
• facebookresearch / semi-discrete-flow
  code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"
  ☆24Updated last year
• nkeriven / random-graph-gnn
  ☆12Updated 3 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆36Updated 2 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆44Updated last year
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated 11 months ago
• ansonb / FeTA_TMLR
  This repository reproduces the results in the paper "How expressive are transformers in spectral domain for graphs?"(published in TMLR)
  ☆11Updated 2 years ago
• ml-jku / quam
  Quantification of Uncertainty with Adversarial Models
  ☆27Updated last year
• ml-jku / VAG-CO
  ☆11Updated 11 months ago
• hedixia / HeavyBallNODE
  ☆13Updated 3 years ago