Weather Forecasting

27 papers with code • 0 benchmarks • 6 datasets

Weather Forecasting is the prediction of future weather conditions such as precipitation, temperature, pressure and wind.

Source: MetNet: A Neural Weather Model for Precipitation Forecasting

Greatest papers with code

NGBoost: Natural Gradient Boosting for Probabilistic Prediction

stanfordmlgroup/ngboost ICML 2020

NGBoost generalizes gradient boosting to probabilistic regression by treating the parameters of the conditional distribution as targets for a multiparameter boosting algorithm.

Weather Forecasting

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

ndrplz/ConvLSTM_pytorch NeurIPS 2015

The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time.

Machine Learning Weather Forecasting

Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks

benedekrozemberczki/pytorch_geometric_temporal 16 Feb 2021

Recurrent graph convolutional neural networks are highly effective machine learning techniques for spatiotemporal signal processing.

Machine Learning Time Series +2

WeatherBench: A benchmark dataset for data-driven weather forecasting

pangeo-data/WeatherBench 2 Feb 2020

Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains.

Weather Forecasting

Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

BruceBinBoxing/Weather_Forecasting 22 Dec 2018

We cast the weather forecasting problem as an end-to-end deep learning problem and solve it by proposing a novel negative log-likelihood error (NLE) loss function.

Machine Learning Weather Forecasting

Verified Uncertainty Calibration

AnanyaKumar/verified_calibration NeurIPS 2019

In these experiments, we also estimate the calibration error and ECE more accurately than the commonly used plugin estimators.

Weather Forecasting

Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere

jweyn/DLWP-CS 15 Mar 2020

The cubed-sphere remapping minimizes the distortion on the cube faces on which convolution operations are performed and provides natural boundary conditions for padding in the CNN.

Weather Forecasting

Deep recurrent Gaussian process with variational Sparse Spectrum approximation

mauriziofilippone/deep_gp_random_features 27 Sep 2019

In this paper we introduce several new Deep recurrent Gaussian process (DRGP) models based on the Sparse Spectrum Gaussian process (SSGP) and the improved version, called variational Sparse Spectrum Gaussian process (VSSGP).

Autonomous Driving Weather Forecasting

SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture

HansBambel/SmaAt-UNet 8 Jul 2020

Weather forecasting is dominated by numerical weather prediction that tries to model accurately the physical properties of the atmosphere.

Weather Forecasting

Deep Learning for Post-Processing Ensemble Weather Forecasts

spcl/deep-weather 18 May 2020

Applied to global data, our mixed models achieve a relative improvement in ensemble forecast skill (CRPS) of over 14%.

Weather Forecasting