MeysamAmirsardari

MeysamAmirsardari's Stars

• tsy935/graphs4mer

  Language:Python498

• KaihuaTang/CiiV-Adversarial-Robustness.pytorch

  The official PyTorch Implementation of the Paper "Adversarial Visual Robustness by Causal Intervention"

  Language:Jupyter Notebook181

• MeysamAmirsardari/robustiou

  to be added soon...

  Language:Jupyter Notebook1

• MeysamAmirsardari/PoseModel

  PoseModel: An Open-Source Toolkit for Accurate and Robust Automated Behavioral Latent Embedding

  Language:Jupyter Notebook51

• ryanayork/TREBLE

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• zhijing-jin/ARTS_TestSet

  This is our ARTS test set, an enriched test set to probe Aspect Robustness of ABSA.

  Language:Python414

• AdaptiveMotorControlLab/CEBRA

  Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA

  Language:Python90877

• Subhajit135/CS236_DGM

  🦍 Stanford CS236 : Deep Generative Models

  9977

• jiangnanboy/gcn_for_prediction_of_protein_interactions

  gcn for prediction of protein interactions，图卷积用于蛋白质相互作用。

  Language:Python223

• yao8839836/text_gcn

  Graph Convolutional Networks for Text Classification. AAAI 2019

  Language:Python1.4k434

• drprojects/DeepViewAgg

  [CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"

  Language:Python22424

• benedekrozemberczki/karateclub

  Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

  Language:Python2.2k246

• paninski-lab/deepgraphpose

  DeepGraphPose

  Language:Python329

• Tiger101010/DAEGC

  PyTorch implementation of Deep Attention Embedding Graph Clustering (19IJCAI) https://www.ijcai.org/Proceedings/2019/0509.pdf

  Language:Python10819

• YingtongDou/GCNN

  The Pytorch Implementation of GCNN model from paper Fake News Detection on Social Media using Geometric Deep Learning

  Language:Python346

• safe-graph/GNN-FakeNews

  A collection of GNN-based fake news detection models.

  Language:Python44090

• aio-libs/aiohttp

  Asynchronous HTTP client/server framework for asyncio and Python

  Language:Python15.1k2k

• ChenNed/CasCN

  Information Diffusion Prediction via Recurrent Cascades Convolution

  Language:Python5011

• MathiasKraus/CascadeLSTM

  A tree-structured neural classifier for detecting misinformation cascades

  Language:Python165

• graphhopper/graphhopper

  Open source routing engine for OpenStreetMap. Use it as Java library or standalone web server.

  Language:Java5.4k1.6k

• shaypal5/awesome-twitter-data

  A list of Twitter datasets and related resources.

  966124

• diogofpacheco/twitter_cascades

  Code to reconstruct Twitter cascades given a set of tweets and a list of followers from the participants in the conversation

  Language:Jupyter Notebook41

• paolazola/Interaction-strength-analysis-to-model-retweet-cascade-graphs

  Language:Python1

• ibaaj/dijkstra-cartography

  Using Dijkstra's algorithm ("finding the shortest paths between nodes in a graph") to draw maps :earth_africa:.

  Language:C++1.2k76

• kinfi4/Kin-Txt

  Kin-TXT is a powerful platform for aggregating, analyzing and visualizing text data from social media.

  Language:JavaScript71

• duke8585/telethon_grabber

  a script to obtain group messages from telegram and store them in a dataframe for later analysis

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• malteheckelen/telegram_scraping

  some simple utilities to work with the telegram api via telethon: mainly getting channel messages of channels that forwarded each other recursively

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• th3unkn0n/TeleGram-Scraper

  telegram group scraper tool. fetch all information about group members

  Language:Python1.5k727

• sadra-barikbin/Attentionist-a-novel-solution-for-structured-sentiment-analysis

  Attentionist. A novel solution for Structured Sentiment Analysis

  Language:Jupyter Notebook11

• estebanpdl/telegram-tracker

  The package connects to Telegram's API to generate JSON files containing data for channels, including information and posts. It allows you to search for specific channels or a set of channels provided in a text file, with one channel per line.

  Language:Python33662