abojchevski / sparse_smoothingLinks
Implementation of the certificates proposed in the paper "Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More"
☆35Updated 2 years ago
Alternatives and similar repositories for sparse_smoothing
Users that are interested in sparse_smoothing are comparing it to the libraries listed below
Sorting:
- Adversarial Attacks on Node Embeddings via Graph Poisoning☆59Updated 5 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Updated 4 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆104Updated 5 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆52Updated 5 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- Implicit Graph Neural Networks☆62Updated 3 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆83Updated 10 months ago
- informal exposition of Weisfeiler-Leman similarity☆28Updated 4 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- Implementation of paper "Transferring Robustness for Graph Neural Network Against Poisoning Attacks".☆20Updated 5 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 3 years ago
- ☆12Updated 4 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆19Updated 11 months ago
- ☆25Updated 4 years ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆30Updated last year
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 years ago
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 3 years ago
- ☆62Updated 4 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 5 years ago
- The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020☆34Updated 4 years ago
- ☆19Updated 2 years ago
- Implementation of the paper "Adversarial Attacks on Graph Neural Networks via Meta Learning".☆149Updated 3 years ago
- A Python implementation of a fast approximation of the Weisfeiler-Lehman Graph Kernels.☆24Updated 6 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆42Updated 3 years ago
- SIGN: Scalable Inception Graph Network☆96Updated 4 years ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆43Updated 2 years ago
- D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019☆139Updated 4 years ago