vcjy2017 Goto Github PK

allennlp

An open-source NLP research library, built on PyTorch.

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bert-pytorch

Google AI 2018 BERT pytorch implementation

cathi

Context-aware Trajectory Embedding and Human Mobility Inference

clustergcn

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

da-rnn

Dual-Stage Attention-Based Recurrent Neural Net for Time Series Prediction

data-preprocess-for-fmm

This project mainly address the map match for larger low sampling GPS trajectory dataset based on the method proposed and developed by Yang and Gidofalvi(2018)

deep-forecast-pytorch

Wind Speed Prediction using LSTMs in PyTorch (https://arxiv.org/pdf/1707.08110.pdf)

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deeplearningfornlpinpytorch

An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.

dmvst_net

包括部分数据预处理以及基于Tensorflow的DMVST_Net模型的实现

dtw

Dynamic Time Warping in Python / C (using ctypes)

gnnpapers

Must-read papers on graph neural networks (GNN)

graph-wavenet

graphsage

Representation learning on large graphs using stochastic graph convolutions.

graphsage-simple

Simple reference implementation of GraphSAGE.

gretel-path-extrapolation

Implementation for the paper "Extrapolating paths with graph neural networks"

hello2017

the first try

imbalance-xgboost

XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

mdvoxelclustering

A voxel based approach for dynamic cluster analysis of molecular dynamics trajectories.

mmskeleton

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

most-frequented-locations

Extract Most Frequented Locations from individual spatio-temporal trajectories

nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

pointnet2-pytorch

A clean PointNet++ segmentation model implementation

predicting-osprey-migration

This project was done as a part of the Applied Machine Learning Course (COMP 551) at McGill University and was done in a group of 3 students. Ospreys are severely affected by pollutants in their environment because they are at the top of their food chain. The population of ospreys in the eastern USA significantly decreased due to DDT use in the middle of the twentieth century. It has since recovered. This project dealt with the basic methodology and results obtained for an osprey data set chosen from Movebank for predicting the migration periodicity and directionality exhibited by these birds as a group and individually. K-means clustering and the Discrete Fourier Transform were used to predict the migration patterns. Long Short-Term Memory was used to predict the future movement of the birds. This analysis could help identify unusual patterns in bird migration trajectories in the future. If unusual patterns present themselves among many birds, the possible pollutant needs to be identified and eliminated from the region. I helped in data extraction and implemented k-means clustering algorithm.

prompt-in-context-learning

Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.

pytorch-batch-attention-seq2seq

PyTorch implementation of batched bi-RNN encoder and attention-decoder.

pytorch_classification

基于pytorch框架的classification万用模板

pytorch_tutorial

《Pytorch模型训练实用教程》中配套代码