wu-lingxia
Follow
Stars
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
A python library for user-friendly forecasting and anomaly detection on time series.
Probabilistic time series modeling in Python
In PyTorch Learing Neural Networks Likes CNN、BiLSTM
Processing and gridding spatial data, machine-learning style
A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.
Python implementation of the rulefit algorithm
Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data
Decode CINRAD (China New Generation Weather Radar) data and visualize.
Layer-wise Relevance Propagation (LRP) for LSTMs.
A Python library for calculating and displaying the skill of model predictions against observations.
Statistical climate downscaling in Python
[NeurIPS 2023] A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
A package for HYSPLIT air parcel trajectory analysis.
Multifractal Detrended Fluctuation Analysis in Python
Python code implementing the power method for Singular Value Decomposition
CINRAD basic data read and process. Draw PPI, RHI, CAPPI, volume rendering and several 3D model of basic data.
Interpolating & distributing MEIC 0.25*0.25 emission inventory onto WRF-Chem grids
Python version of the Multivariate Empirical Mode Decomposition algorithm
Code examples for using the originpro Python package to interact with Origin software.
pyEOF: Empirical Orthogonal Function (EOF) analysis and Rotated EOF analysis in Python
PyTorch implementation of probabilistic deep forecast applied to air quality.
An advancement on the EEMD method, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) allows for a granular spectral separation of the Intrinsic Mode Functions and a more …