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neural_prophet

NeuralProphet - A simple forecasting model based on Neural Networks in PyTorch

neuralrdes

Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)

newage-jgrass

NewAge-JGrass repository

ngboost

Natural Gradient Boosting for Probabilistic Prediction

nixtla

Automated time series processing and forecasting.

nonconformist

Python implementation of the conformal prediction framework.

numerical-linear-algebra

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

nxarray

NeXus input/output capability for xarray

ogh_summer_school_2023

Links and slides from the OpenGeoHub summer school 2023

ogs5

Official repository of the OpenGeoSys THM/C simulator

oms_project_wb

paleo-asia

Data and code for the paper "Coherent streamflow variability in Monsoon Asia over the past eight centuries---links to oceanic drivers"

pandas-videos

Jupyter notebook and datasets from the pandas Q&A video series

paramtest

R package for varying parameters in simulations or other iterative processes

pastas

:spaghetti: Pastas is an open-source Python framework for the analysis of groundwater time series.

pastastore

:spaghetti: :convenience_store: Tools for managing timeseries and Pastas models

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

pcr-globwb_model

PCR-GLOBWB (PCRaster Global Water Balance) is a large-scale hydrological model intended for global to regional studies and developed at the Department of Physical Geography, Utrecht University (Netherlands). Contact: Edwin Sutanudjaja ([email protected]).

petrelli-m

Config files for my GitHub profile.

pga_lstm

Physics Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modelling

pgnn

Physics-guided Neural Networks (PGNN) : An Application In Lake Temperature Modelling

phygnn

physics-guided neural networks (phygnn)

physics-based-deep-learning

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

physics_prediction

Codes for paper "Flexible Neural Representation for Physics Prediction".

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

podaacpy

A python utility library for interacting with NASA JPL's PO.DAAC

powerlawlstm

pp-s2s

ppi_py

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

probabilistic_app

Probabilistic predictions Webapp + R package