ArmanBehnam

ArmanBehnam's Stars

• BVLC/caffe

  Caffe: a fast open framework for deep learning.

  Language:C++34.1k2.1k4.8k18.7k

• pyg-team/pytorch_geometric

  Graph Neural Network Library for PyTorch

  Language:Python21.1k2523.5k3.6k

• NVlabs/stylegan

  StyleGAN - Official TensorFlow Implementation

  Language:Python14.1k45003.2k

• naganandy/graph-based-deep-learning-literature

  links to conference publications in graph-based deep learning

  Language:Jupyter Notebook4.7k25014773

• graphdeeplearning/benchmarking-gnns

  Repository for benchmarking graph neural networks

  Language:Jupyter Notebook2.5k5868452

• tkipf/gae

  Implementation of Graph Auto-Encoders in TensorFlow

  Language:Python1.6k3578351

• RexYing/gnn-model-explainer

  gnn explainer

  Language:Python8602231173

• matnbaz/matnbaz

  Source-code for the "matnbaz" project (Archived)

  Language:TypeScript58774224

• aamini/evidential-deep-learning

  Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

  Language:Python431171697

• DaehanKim/vgae_pytorch

  This repository implements variational graph auto encoder by Thomas Kipf.

  Language:Python3832972

• diningphil/gnn-comparison

  Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020

  Language:Python38082053

• fishmoon1234/DAG-GNN

  Language:Python28672370

• d909b/cxplain

  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.

  Language:Python1268636

• Mofid-AI/persian-nlp-benchmark

  A benchmark for evaluation and comparison of various NLP tasks in Persian language.

  Language:Jupyter Notebook73613

• wanyu-lin/ICML2021-Gem

  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."

  Language:Jupyter Notebook64269

• pralab/Fast-Minimum-Norm-FMN-Attack

  Foolbox implementation for NeurIPS 2021 Paper: "Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints".

  Language:Jupyter Notebook26324

• zecevic-matej/Towards-Tractable-Neural-Causal-Model

  Official code repository to the corresponding paper.

  Language:Python237

• abojchevski/graph_cert

  Certifiable Robustness to Graph Perturbations

  Language:Jupyter Notebook13257

• danielzuegner/robust-gcn-structure

  Language:Python12213

• CausalAILab/NCMCounterfactuals

  Language:Python71

• SC-Lab-Go/BugGraph

  Language:Python7102

• Nikronic/NLP-Fall18-UOG

  In this repository, We implemented a Statistical NLP model to predict news agency, news tags, etc as final project of NLP course in university of Guilan

  Language:Jupyter Notebook5341

• parthnatekar/Neural_Causal_Modelling

  Delineating Causality in Neural Networks

  Language:Python5303

• bitsecurerlab/DeepMem

  A graph-based deep learning tool that can recognizes the kernel objects from raw memory dumps.

  Language:Python3100

• ageron/keras-io

  Keras documentation, hosted live at keras.io

  Language:Jupyter Notebook2102

• BenyaminGhN/AIOS-Artificial-Intelligence-Operating-Systems-Presentation-Slides

  This is a futuristic point of view of next-generation operating systems based on artificial intelligence

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