Public implementation of the Convolutional Motif Kernel Network (CMKN) architecture

Last update: Nov 17, 2021

Related tags

Overview

CMKN

Implementation of the convolutional motif kernel network (CMKN) introduced in Ditz et al., "Convolutional Motif Kernel Network", 2021.

Testing

You can run the unit-tests by executing

$ python -m unittest

from the root of the project. The tests include some standard problems of pulse propagation in nonlinear media. During the tests an interactive plotter demonstrating the integration results will be shown. Unfortunately, at the moment it is not possible to disable it, so running tests in a headless setup is not straightforward.

Documentation

The documentation is written with sphinx. You can build it by running

$ cd doc && make html

from the root of the project. The entry point for the documentation will be placed in doc/_build/html/index.html which you can open with a browser of your choice.

You might also like...

Official public repository of paper "Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation"

Intention Adaptive Graph Neural Network (IAGNN) This is the official repository of paper Intention Adaptive Graph Neural Network for Category-Aware Se

9 Nov 22, 2022

Implementation of character based convolutional neural network

Character Based CNN This repo contains a PyTorch implementation of a character-level convolutional neural network for text classification. The model a

248 Nov 21, 2022

A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).

SGCN ⠀ A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018). Abstract Due to the fact much of today's data can be represented as

251 Nov 30, 2022

A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

66 Nov 30, 2022

An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"

Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional

23 Aug 20, 2022

Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia

3 Apr 12, 2022

Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"

SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila

1 Nov 26, 2021

An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset

关于实现的一点说明山东大学 2020级苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数： resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a，返回一个$lenb\times lenb$的方阵。因

2 Aug 29, 2022

Code for Mesh Convolution Using a Learned Kernel Basis

Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY

35 Jan 3, 2023

Releases(v0.1)

v0.1(Nov 15, 2021)

This release is the first version of convolutional motif kernel networks. The code includes PyTorch objects to construct a CMKN model and handle input data. Furthermore, methods to analyze and interpret a trained CMKN model are included as well as routines to prepare HIVdb's data for experiments. A first documentation of the project can be build with sphinx.
Source code(tar.gz)
Source code(zip)

Owner

GitHub Repository

机器学习、深度学习、自然语言处理等人工智能基础知识总结。

说明机器学习、深度学习、自然语言处理基础知识总结。目前主要参考李航老师的《统计学习方法》一书，也有一些内容例如XGBoost、聚类、深度学习相关内容、NLP相关内容等是书中未提及的。

445 Dec 12, 2022

ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives

Status: Under development (expect bug fixes and huge updates) ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectiv

37 Dec 28, 2022

SimulLR - PyTorch Implementation of SimulLR

PyTorch Implementation of SimulLR There is an interesting work[1] about simultan

11 Dec 22, 2022

CVPR 2021 Challenge on Super-Resolution Space

Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of

104 Oct 26, 2022

EEGEyeNet is benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty

Introduction EEGEyeNet EEGEyeNet is a benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty. Overview T

23 Dec 22, 2022

Learning to Estimate Hidden Motions with Global Motion Aggregation

Learning to Estimate Hidden Motions with Global Motion Aggregation (GMA) This repository contains the source code for our paper: Learning to Estimate

221 Dec 18, 2022

Video Frame Interpolation with Transformer (CVPR2022)

VFIformer Official PyTorch implementation of our CVPR2022 paper Video Frame Interpolation with Transformer Dependencies python = 3.8 pytorch = 1.8.0

63 Dec 16, 2022

An educational AI robot based on NVIDIA Jetson Nano.

JetBot Looking for a quick way to get started with JetBot? Many third party kits are now available! JetBot is an open-source robot based on NVIDIA Jet

2.6k Dec 29, 2022

Facilitating Database Tuning with Hyper-ParameterOptimization: A Comprehensive Experimental Evaluation

A Comprehensive Experimental Evaluation for Database Configuration Tuning This is the source code to the paper "Facilitating Database Tuning with Hype

9 Oct 29, 2022

AirCode: A Robust Object Encoding Method

AirCode This repo contains source codes for the arXiv preprint "AirCode: A Robust Object Encoding Method" Demo Object matching comparison when the obj

30 Dec 09, 2022

PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."

PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple

54 Dec 19, 2022