Python Hierarchical-attention-networks Resources

Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran

BERT Attention Analysis This repository contains code for What Does BERT Look At? An Analysis of BERT's Attention. It includes code for getting attent

structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for

The Story of Heads This is the official repo for the following papers: (ACL 2019) Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy

The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS

Continuous Sparsification Implementation of Continuous Sparsification (CS), a method based on l_0 regularization to find sparse neural networks, propo

New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code

PyTorch implementation of BERT and PALs Introduction Work by Asa Cooper Stickland and Iain Murray, University of Edinburgh. Code for BERT and PALs; mo

#Sentic GCN Introduction This repository was used in our paper: Aspect-Based Sentiment Analysis via Affective Knowledge Enhanced Graph Convolutional N

Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga

Attention Is All You Need Paper Implementation This is my from-scratch implementation of the original transformer architecture from the following pape

Multipath-Load-Balancing Method of managing incoming traffic by distributing and sharing load fairly among multiple routes from source to destination

Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag

dispersion-score Official implementation of 3DV 2021 Paper A Dataset-dispersion Perspective on Reconstruction versus Recognition in Single-view 3D Rec

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks Requirements python 0.10+ rdkit 2020.03.3.0 biopython 1.78 openbabel 2.4

PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read

DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n

Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the

LMMNN Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks This is the working dire

Representation Learning on Spatial Networks This repository is the official implementation of Representation Learning on Spatial Networks. Training Ex

Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks This is the official code for DyReg model inroduced in Discovering Dyna

PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int

Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N

ReFine: Multi-Grained Explainability for GNNs We are trying hard to update the code, but it may take a while to complete due to our tight schedule rec

EIGNN: Efficient Infinite-Depth Graph Neural Networks The official implementation of EIGNN: Efficient Infinite-Depth Graph Neural Networks (NeurIPS 20

Directed Graph Contrastive Learning Paper | Poster | Supplementary The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this

Configurations Change HOME_PATH in CONFIG.py as the current path Data Prepare CENSINCOME Download data Put census-income.data and census-income.test i

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

NeuroMLR: Robust & Reliable Route Recommendation on Road Networks This repository is the official implementation of NeuroMLR: Robust & Reliable Route

Conditional Generation Using Polynomial Expansions Official implementation of the conditional image generation experiments as described on the NeurIPS

lpips-pytorch Description Developing perceptual distance metrics is a major topic in recent image processing problems. LPIPS[1] is a state-of-the-art

This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).

PyDGN Wiki Description This is a Python library to easily experiment with Deep Graph Networks (DGNs). It provides automatic management of data splitti

Artificial Neural Network This repository contain implementation of Artificial Neural Network Algorithm in several programming languanges and framewor

Adjusting for Autocorrelated Errors in Neural Networks for Time Series This repository is the official implementation of the paper "Adjusting for Auto

Long Expressive Memory for Sequence Modeling This repository contains the implementation to reproduce the numerical experiments of the paper Long Expr

Swin-Transformer Swin-Transformer is basically a hierarchical Transformer whose representation is computed with shifted windows. For more details, ple

Orchard Dataset This repository contains the code used for generating the Orchard Dataset, as seen in the Multi-Hierarchical Reasoning in Sequences: S

ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le

NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B

SMU_pytorch A Pytorch Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/ab

Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P

Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,

FRANe Unsupervised Feature Ranking via Attribute Networks (FRANe) converts a dataset into a network (graph) with nodes that correspond to the features

ContourletNet: A Generalized Rain Removal Architecture Using Multi-Direction Hierarchical Representation (Accepted by BMVC'21) Abstract: Images acquir

PHDimGeneralization Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021. Overvie

Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks Official implementation of paper Towards Practic

Hierarchical Motion Encoder-Decoder Network for Trajectory Forecasting (HMNet) Our paper: https://arxiv.org/abs/2111.13324 We will release the complet

Image Captioning using CNN ,LSTM and Attention This is a deeplearning model which tries to summarize an image into a text . Installation Install this

A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks without the use of any outside machine learning libraries - all from scratch.

Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-identification

PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

Study-CSRNet-pytorch This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model

Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei

CNN Explainer An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs) For more information,

Welcome to labelpix 👋 labelpix is a graphical image labeling interface for drawing bounding boxes. 🏠 Homepage Install pip install -r requirements.tx

MobileNetV1-V2，MobileNeXt，GhostNet，AdderNet，ShuffleNetV1-V2，Mobile+ViT etc. ⭐⭐⭐⭐⭐

GCA-Matting: Natural Image Matting via Guided Contextual Attention The source codes and models of Natural Image Matting via Guided Contextual Attentio

HOP-Matting Official repository for Hierarchical Opacity Propagation for Image Matting 🚧 🚧 🚧 Under Construction 🚧 🚧 🚧 🚧 🚧 🚧   Coming Soon   

Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration

PCAN for Multiple Object Tracking and Segmentation This is the offical implementation of paper PCAN for MOTS. We also present a trailer that consists

mPose3D, a mmWave-based 3D human pose estimation model.

CoaDTI Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2 Abstract Environment The test was conducted i

Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is

Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp

DHF1K =========================================================================== Wenguan Wang, J. Shen, M.-M Cheng and A. Borji, Revisiting Video Sal

AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

h3-pyspark: Uber's H3 Hexagonal Hierarchical Geospatial Indexing System in PySpark PySpark bindings for the H3 core library. For available functions,

SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph

Official code of APHYNITY Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting (ICLR 2021, Oral) Yuan Yin*, Vincent Le Guen*

Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J

Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne

Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw

Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD

Delve is a Python package for analyzing the inference dynamics of your PyTorch model.

DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

ENN Incubator Collection of in-progress libraries for entity neural networks: Neural Network Architectures for Structured State Entity Gym: Abstractio

Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

GLANet The code for Global and Local Alignment Networks for Unpaired Image-to-Image Translation arxiv Framework: visualization results: Getting Starte

lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

English | 简体中文 Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat

Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,

networkgen A python module to create random networks using network models Usage $

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay