310 Open source projects that are alternatives of or similar to stagin

Graph theory analysis of brain MRI data

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data

VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.

Official code of "Towards Multi-Grained Explainability for Graph Neural Networks" (2021 NeurIPS)

fmriflows is a consortium of many (dependent) fMRI analysis pipelines, including anatomical and functional pre-processing, univariate 1st and 2nd-level analysis, as well as multivariate pattern analysis.

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.

nlp lecture-notes and source code

Software platform for clinical neuroimaging studies

This shows a basic implementation of the global nearest neighbour (GNN) multi target Tracker. Kalman filter is used for Tracking and Auction Algorithm for determining the assignment of measurments to filters.

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

A paper list of research about social knowledge graph

Attention mechanism

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

Method container for computational neuroscience on brains.

Framework for the reproducible processing of neuroimaging data with deep learning methods

Brain extraction in presence of abnormalities, using single and multiple MRI modalities

[IEEE TNSRE] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"

Attentional Learning of Trash Classification

hypergraph representation learning, graph neural network

一个基于深度学习的中文聊天机器人，这里有详细的教程与代码，每份代码都有详细的注释，作为学习是美好的选择。A Chinese chatbot based on deep learning.

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

Public release of The Cole-Anticevic Brain-wide Network Partition (CAB-NP)

multi-label，classifier，text classification，多标签文本分类，文本分类，BERT，ALBERT，multi-label-classification，seq2seq，attention，beam search

An index of recommendation algorithms that are based on Graph Neural Networks.

Recalling node properties from a knowledge graph

Enhanced BiLSTM Inference Model for Natural Language Inference

A real-time GNN-based method. Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning

A PyTorch Implementation of "Attention Is All You Need"

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

Word Sense Disambiguation using Word Specific models, All word models and Hierarchical models in Tensorflow

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

Contextual AI adds explainability to different stages of machine learning pipelines - data, training, and inference - thereby addressing the trust gap between such ML systems and their users. It does not refer to a specific algorithm or ML method — instead, it takes a human-centric view and approach to AI.

[ICCV 2021] TRAR: Routing the Attention Spans in Transformers for Visual Question Answering -- Official Implementation

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Code and data for Zhang, Lengersdorff et al. (2020)

Utility functions for working with DICOM and BIDS neuroimaging data

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Implementation of the paper Recurrent Independent Mechanisms (https://arxiv.org/pdf/1909.10893.pdf)

NeuroInformatics Database

List of Publications in Graph Contrastive Learning

Compose chunk operators to create a pipeline for local or distributed petabyte-scale computation

The ENIGMA Toolbox is an open-source repository for accessing 100+ ENIGMA statistical maps, visualizing cortical and subcortical surface data, and relating neuroimaging findings to micro- and macroscale brain organization. 🤠

MATLAB/Octave GIfTI Library

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.

Multi-head attention in PyTorch

Predict materials properties using only the composition information!

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

A Pytorch implementation of CVPR 2020 paper: Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Codes for WWW'18 Paper-DeepMove: Predicting Human Mobility with Attentional Recurrent Network

Deep Learning and Machine Learning mini-projects. Current Project: Deepmind Attentive Reader (rc-data)