Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach

Related tags

Deep LearningDTMP
Overview

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach

This is the implementation of traffic prediction code in DTMP based on PyTorch.

structure of the code:

  • data folder: storing PEMSD4 and PEMSD8 dataset. You may refer to ASTGCN for more details;
  • lib folder: some methods for data loading and processing from AGCRN;
  • utils.py: method of loading adjacency graph;
  • model.py: implementation of Anet;
  • train.py, run.py: train and run the model.

You can use python run.py --dataset PEMSD4 --num_nodes 307 command to run the code.

Owner
chenxin
chenxin
Paaster is a secure by default end-to-end encrypted pastebin built with the objective of simplicity.

Follow the development of our desktop client here Paaster Paaster is a secure by default end-to-end encrypted pastebin built with the objective of sim

Ward 211 Dec 25, 2022
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

The Hypersim Dataset For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real i

Apple 1.3k Jan 04, 2023
This repository contains implementations and illustrative code to accompany DeepMind publications

DeepMind Research This repository contains implementations and illustrative code to accompany DeepMind publications. Along with publishing papers to a

DeepMind 11.3k Dec 31, 2022
This package is for running the semantic SLAM algorithm using extracted planar surfaces from the received detection

Semantic SLAM This package can perform optimization of pose estimated from VO/VIO methods which tend to drift over time. It uses planar surfaces extra

Hriday Bavle 125 Dec 02, 2022
Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX.

snc4onnx Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools 1.

Katsuya Hyodo 8 Oct 13, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"

Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design". CoordAttention tensorflow slim

Billy 9 Aug 22, 2022
PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"

Smoothed Mutual Information ``Lower Bound'' Estimator PyTorch implementation for the ICLR 2020 paper Understanding the Limitations of Variational Mutu

50 Nov 09, 2022
Multi-Template Mouse Brain MRI Atlas (MBMA): both in-vivo and ex-vivo

Multi-template MRI mouse brain atlas (both in vivo and ex vivo) Mouse Brain MRI atlas (both in-vivo and ex-vivo) (repository relocated from the origin

8 Nov 18, 2022
A minimal implementation of Gaussian process regression in PyTorch

pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b

Sangwoong Yoon 38 Nov 25, 2022
Adaptive Attention Span for Reinforcement Learning

Adaptive Transformers in RL Official implementation of Adaptive Transformers in RL In this work we replicate several results from Stabilizing Transfor

100 Nov 15, 2022
Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.

NOTE: This is still being developed! Setup notes This document uses Jeff Sackmann's tennis data. You can obtain it as follows: git clone https://githu

Martin Ingram 1 Jan 20, 2022
Official PyTorch Implementation of Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity

UnRigidFlow This is the official PyTorch implementation of UnRigidFlow (IJCAI2019). Here are two sample results (~10MB gif for each) of our unsupervis

Liang Liu 28 Nov 16, 2022
Improving Non-autoregressive Generation with Mixup Training

MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p

7 Nov 22, 2022
Existing Literature about Machine Unlearning

Machine Unlearning Papers 2021 Brophy and Lowd. Machine Unlearning for Random Forests. In ICML 2021. Bourtoule et al. Machine Unlearning. In IEEE Symp

Jonathan Brophy 213 Jan 08, 2023
Architecture Patterns with Python (TDD, DDD, EDM)

architecture-traning Architecture Patterns with Python (TDD, DDD, EDM) Chapter 5. 높은 기어비와 낮은 기어비의 TDD 5.2 도메인 계층 테스트를 서비스 계층으로 옮겨야 하는가? 도메인 계층 테스트 def

minsung sim 2 Mar 04, 2022
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu

Varun Nair 37 Dec 30, 2022
PyMatting: A Python Library for Alpha Matting

Given an input image and a hand-drawn trimap (top row), alpha matting estimates the alpha channel of a foreground object which can then be composed onto a different background (bottom row).

PyMatting 1.4k Dec 30, 2022
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"

DRNet for Video Indvidual Counting (CVPR 2022) Introduction This is the official PyTorch implementation of paper: DR.VIC: Decomposition and Reasoning

tao han 35 Nov 22, 2022
Face Recognize System on camera AI OAK1

FRS on OAK1 Face Recognize System on camera OAK1 This project contains our work that deploy on camera OAK1 Features Anti-Spoofing Face detection Face

Tran Anh Tuan 6 Aug 08, 2022