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Traffic Prediction

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하위 태스크: 1
평가표: 33
보존된 평가 기록: 192

Traffic Prediction is a task that involves forecasting traffic conditions, such as the volume of vehicles and travel time, in a specific area or along a particular road. This task is important for optimizing transportation systems and reducing traffic congestion.

<span style="color:grey; opacity: 0.6">( Image credit: BaiduTraffic )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/zhengchuanpan/GMAN

공식 코드

GMAN: A Graph Multi-Attention Network for Traffic Prediction

https://github.com/zhiyongc/Seattle-Loop-Data

공식 코드

Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting

https://github.com/zhyliu00/fdti

공식 코드

FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph

https://github.com/zxc2012/flowdistill

공식 코드

FlowDistill: Scalable Traffic Flow Prediction via Distillation from LLMs

https://github.com/2023-MindSpore-1/ms-code-197

Sequence to Sequence Learning with Neural Networks

https://github.com/2023-MindSpore-1/ms-code-198

Sequence to Sequence Learning with Neural Networks

https://github.com/2023-MindSpore-1/ms-code-200

Sequence to Sequence Learning with Neural Networks

https://github.com/2023-MindSpore-1/ms-code-61

Sequence to Sequence Learning with Neural Networks

https://github.com/2023-MindSpore-1/ms-code-62

Sequence to Sequence Learning with Neural Networks

https://github.com/2023-MindSpore-4/Code16/tree/main/baopeng/HW-GTGCN

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

https://github.com/2jungeuni/stgcn-pytorch

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

https://github.com/AMNAALMGLY/NLP

Sequence to Sequence Learning with Neural Networks

https://github.com/Aguin/STGCN-PyTorch

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

https://github.com/ApolloScapeAuto/dataset-api

TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

https://github.com/ArushiSinghal/NMT-assignment1

Sequence to Sequence Learning with Neural Networks

https://github.com/ArushiSinghal/Neural-Machine-Translation

Sequence to Sequence Learning with Neural Networks

https://github.com/ArushiSinghal/Neural-Machine-Translation-English-Hindi-for-domain-data

Sequence to Sequence Learning with Neural Networks

https://github.com/BinqingWu/2019-ZJU_SummerResearch

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/CGCL-codes/naturalcc

Sequence to Sequence Learning with Neural Networks

https://github.com/CYBruce/STAWnet

https://github.com/Chatha-Sphere/pno-ai

Sequence to Sequence Learning with Neural Networks

https://github.com/Davidham3/ASTGCN

https://github.com/Davidham3/STSGCN

https://github.com/E666GT/TrafficPredictionNN

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

https://github.com/EDAPINENUT/CLCRN

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/EuphoriaYan/ChatRobot-For-Keras2

Sequence to Sequence Learning with Neural Networks

https://github.com/GestaltCogTeam/STID

Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting

https://github.com/Guillem96/pointer-nn-pytorch

Sequence to Sequence Learning with Neural Networks

https://github.com/HiddeKanger/SCINet

SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction

https://github.com/IvanVassi/Seq2Seq-w-attention-dialogue-model

Sequence to Sequence Learning with Neural Networks

https://github.com/JRC1995/Abstractive-Summarization

Sequence to Sequence Learning with Neural Networks

https://github.com/JiahuiSun/Exp-Graph-WaveNet

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

https://github.com/Kaimaoge/IGNNK

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/KimMeen/DCRNN

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

https://github.com/LeiBAI/STG2Seq

STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting

https://github.com/LucaHermes/lightweight-motion-forecasting

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.