Train and visualize Hierarchical Attention Networks
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Updated
Jun 29, 2018 - Python
Train and visualize Hierarchical Attention Networks
Code for A Hierarchical Model for Data-to-Text Generation (Rebuffel, Soulier, Scoutheeten, Gallinari; ECIR 2020)
Hierarchical Attention Networks for Document Classification in Keras
[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"
PyTorch Implementation of Deep Hierarchical Classification for Category Prediction in E-commerce System
Message Passing Attention Networks for Document Understanding
This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029
[WWW 2023] The source code of "Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning"
A Unified RNA Sequencing Model (URSM) for joint analysis of single cell and bulk RNA-seq data.
A toolbox for inference of mixture models
Code for our work "Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach"
[NeurIPS 2022] The implementation for the paper "Equivariant Graph Hierarchy-Based Neural Networks".
Python code of the Decadal and Hierarchical Markov Chain (DHMC) model for stochastic simulation of daily rainfall
Hierarchical image classification model for fashion commerce items based on EfficientNet-b4 and LCPN (Local Classifier per Parent Node) technique.
Code for the ACL2022 main conference paper "A Variational Hierarchical Model for Neural Cross-Lingual Summarization"
Trying out different probabilistic programming packages on the same statistical model
A hierarchical classification system based on traditional machine learning models (LR, SVC, GBDT, RF) and deep learning models (LSTM + Attention)
Deep hierarchical models combined with Markov random fields.
An implementation of the closure table pattern in Python + SQL
Hierarchical modeling in TensorFlow layers
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