Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
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Updated
Dec 9, 2024 - Python
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
tsl: a PyTorch library for processing spatiotemporal data.
[NeurIPS 2023] A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
About Code release for "Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models" (ICLR 2025)
Code for the TMLR 2023 paper "GRAM-ODE: Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting"
STF: A beginner-friendly Spatio-Temporal Forecasting framework for video prediction and radar extrapolation. Includes ConvLSTM, PredRNN, SimVP, UNet, STLight, etc...
(Journal of Hydrology 2026) Large-scale urban flood modeling and zero-shot high-resolution generalization with LarNO
An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution
UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction (ACM SIGSPATIAL 2025)
Code, logs, and final models for SIGSPATIAL SpatialEpi '22: Spatiotemporal Disease Case Prediction using Contrastive Predictive Coding.
Julia implementation of cross-scale reservoir computing for high-dimensional spatiotemporal forecasting. Validated on global sea-surface temperature and chaotic dynamics, achieving low error forecasts up to 8 Lyapunov times on Kuramoto-Sivashinsky. Neurocomputing (2026).
"Evaluation procedures for forecasting with spatio-temporal data" -- Mathematics (MDPI) 2021
Deep learning model for forecasting the spatiotemporal evolution of fluid-induced microearthquakes
Neural Cellular Automata For Large Scale Spatio-Temporal Forecasting
GNN for spatiotemporal Forecasting using Extreme Value Theory
code for "Spatiotemporal Predictive Models for Irregularly Sampled Time Series"
Repository ini berisi partisipasi saya dalam kompetisi ADIKARA 2024 - Data Mining Competition. Repository ini terkait mengembangkan model prediksi Food Price Index menggunakan dataset spatiotemporal.
Official repository for "IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model" (2024 IEEE CAMAD)
Experimental evaluation of one baseline LSTM and two spatiotemporal models---STGCN and GCN-LSTM---for traffic forecasting using the PEMS-BAY dataset.
A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎,预测万物
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