Lynda-Starkus
PhD Student @Univ. Gustave Eiffel (GRETTIA-COSYS) & TransportLab @Univ. Sydney | UE MSCA-CLEARDOC fellow | Eng. & MsC in Computer science
Université Gustave Eiffel Paris, France
Lynda-Starkus's Stars
xai-org/grok-1
Grok open release
princeton-nlp/SWE-agent
SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]
PKU-YuanGroup/Open-Sora-Plan
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
SJTU-IPADS/PowerInfer
High-speed Large Language Model Serving on PCs with Consumer-grade GPUs
google/gemma.cpp
lightweight, standalone C++ inference engine for Google's Gemma models.
lehaifeng/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
pollen-robotics/dtw
DTW (Dynamic Time Warping) python module
VeritasYin/STGCN_IJCAI-18
[IJCAI'18] Spatio-Temporal Graph Convolutional Networks
twitter-research/tgn
TGN: Temporal Graph Networks
sail-sg/Adan
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
Nixtla/hierarchicalforecast
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
guoshnBJTU/ASTGCN-2019-pytorch
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version
hazdzz/STGCN
The PyTorch implementation of STGCN.
lucidrains/iTransformer
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
zhengchuanpan/GMAN
GMAN: A Graph Multi-Attention Network for Traffic Prediction (GMAN, https://fanxlxmu.github.io/publication/aaai2020/) was accepted by AAAI-2020.
DanieleGammelli/variational-poisson-rnn
Official implementation of "Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management"
Evens1sen/Deep-NYC-Taxi-Bike
The repo for the ITSC 2022 paper "Forecasting Regional Multimodal Transportation Demand with Graph Neural Networks: An Open Dataset"
FrancesZhou/GCNTrafficPrediction
pjeena/Traffic-Flow-Prediction-in-the-city-of-Paris-using-LSTM
This app forecasts the live traffic for the next 3 hours in the famous streets of Paris. Additionally, it also provides statistics for the historial traffic data such as distribution of traffic among 2 wheelers and 4 wheelers, most busiest junction etc.
jonpappalord/crowd_flow_prediction
SNCFdevelopers/Pypixgrid
Pypixgrid permet de générer des tuiles vectorielles pour l'exploration de jeux de données spatio-temporels massifs
liangchunyaobing/STMRGNN
Code for Liang, Y., Huang, G., Zhao, Z. (2022). Joint demand prediction for multimodal systems: A multi-task multi-relational spatiotemporal graph neural network approach. Transportation Research Part C: Emerging Technologies, 140, 103731.
jamespfennell/subwaydata.nyc
Source code for subwaydata.nyc ETL pipeline and website
joeyleehk/IrConv-LSTM
csjiezhao/TSIN
nkuweili/MGEGFP
A multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN
srushtii-m/Jersey-City-CitiBike-Demand-Prediction
Analyzing and predicting the demand for bikes using a Spatio-Temporal Graph Convolutional Network (STGCN) model.
urbanis/gbfs-paris-scooters-analysis
Alabouchsalaheddine/VELIB_RIDES_FLOW
In this notebook we will see how we can get to the rides flow of the Velib bikes only by using the public API
jwoLondon/tripParisVis
Visualization and analysis of Paris cycling patterns