Learning in infinite dimension with neural operators.

Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.

A hierarchical modeling framework to discover new machine learning-based equations for cloud cover, including symbolic regression

High-Performance Symbolic Regression in Python and Julia

Code used to produce the analyses and figures of the paper: "Improving climate model skill over High Mountain Asia by adapting snow cover parameterization to complex topography areas"

The matplotlib Animation Extension

This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.

A living benchmark framework for symbolic regression

Genetic Programming version of GOMEA. Also includes standard tree-based GP, and Semantic Backpropagation-based GP

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Physical Symbolic Optimization

Sky view and terrain configuration factors

Energy Exascale Earth System Model source code. NOTE: use "maint" branches for your work. Head of master is not validated.

Community Terrestrial Systems Model (includes the Community Land Model of CESM)

Probabilistic Downscaling of Climate Variables Using Denoising Diffusion Probabilistic Models

The Elements of GANs code repository

Clean, easier to use version of the downscaling cGAN

The list of common abbreviations in program codes.

Calculate black-sky, white-sky, and actual albedo from MODIS MCD43A1 BRDF parameters product with custom solar zenith angle and solar optical depth inputs. Input and output in NetCDF format.

Ruby/Python bindings for CDO

High-performance Terrain and Hydrology Analysis

A lower-level API for Machine Learning inference in operations

The Common Land Model

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

An Adapter aimed for using a PyTorch model directly from a Fortran program

PyDA: A hands-on introduction to dynamical data assimilation with Python

Code repo for publication at https://hess.copernicus.org/articles/26/5085/2022/

为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…

Physics-informed neural networks for the Richardson-Richards equation

🎨 A succinct matplotlib wrapper for making beautiful, publication-quality graphics