Browse > Miscellaneous > Weather Forecasting

# Weather Forecasting Edit

8 papers with code · Miscellaneous

No evaluation results yet. Help compare methods by submit evaluation metrics.

# NGBoost: Natural Gradient Boosting for Probabilistic Prediction

8 Oct 2019stanfordmlgroup/ngboost

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

532

# Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

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

522

# WeatherBench: A benchmark dataset for data-driven weather forecasting

2 Feb 2020pangeo-data/WeatherBench

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

129

# Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

22 Dec 2018BruceBinBoxing/WF

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.

39

# Verified Uncertainty Calibration

An alternative method, histogram binning, has measurable calibration error but is sample inefficient---it requires $O(B/\epsilon^2)$ samples, compared to $O(1/\epsilon^2)$ for scaling methods, where $B$ is the number of distinct probabilities the model can output.

17

# Verified Uncertainty Calibration

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

17

# STConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for Weather Forecasting

30 Nov 2019MLRG-CEFET-RJ/stconvs2s

Applying machine learning models to meteorological data brings many opportunities to the Geosciences field, such as predicting future weather conditions more accurately.

6

# Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network

30 May 2019luoye2333/ResNetLSTM

Wind energy resource quantification, air pollution monitoring, and weather forecasting all rely on rapid, accurate measurement of local wind conditions.

2