A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.

Last update: Apr 29, 2022

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Overview

CCasGNN

A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.

Dataset

We publish the example of processed dataset. Each "list" represents the cascade information. It contains edges, features, nodes(the order of diffusion)

Downlowd link: https://drive.google.com/drive/folders/13k2yKJhRSgGOP9GSBJG7aTsS90JwG337?usp=sharing

The original dataset can be download at: https://www.aminer.cn/data-sna#Twitter-Dynamic-Net, https://www.aminer.cn/citation

Owner

GitHub Repository

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Code for our paper: Online Variational Filtering and Parameter Learning

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A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.

Related tags

Overview

CCasGNN

Dataset

Owner

Generalized Proximal Policy Optimization with Sample Reuse (GePPO)

PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

This is a JAX implementation of Neural Radiance Fields for learning purposes.

Experiments for Fake News explainability project

Implements Gradient Centralization and allows it to use as a Python package in TensorFlow

Code for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions"

Efficient Two-Step Networks for Temporal Action Segmentation (Neurocomputing 2021)

A Kaggle competition: discriminate gender based on handwriting

Fermi Problems: A New Reasoning Challenge for AI

Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capability)

Deep Sketch-guided Cartoon Video Inbetweening

Official implementation for the paper: Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Code for our paper: Online Variational Filtering and Parameter Learning

Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166

Human motion synthesis using Unity3D

SiamMOT is a region-based Siamese Multi-Object Tracking network that detects and associates object instances simultaneously.

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation

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Sibur challange 2021 competition - 6 place

The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".