TiaHao

DL4ES

FourierKAN

pykan

Kolmogorov Arnold Networks

beaapi

A Python library library to make it easier to retrieve and work with BEA data.

SkillMetrics

A Python library for calculating and displaying the skill of model predictions against observations.

seq2seq

Sequence to Sequence Learning with Keras

tsai

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

keras-attention

Keras Attention Layer (Luong and Bahdanau scores).

deepsensor

A Python package for tackling diverse environmental prediction tasks with NPs.

smt

Surrogate Modeling Toolbox

MAGNets

A Python package to aggregate and reduce water distribution network models

GNN_StateEstimation_WDS

Graph neural networks for state estimation in water distribution systems

FEDformer

YLearn

YLearn, a pun of "learn why", is a python package for causal inference

causalml

Uplift modeling and causal inference with machine learning algorithms

StableNet

Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".

tigramite

Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-causality-data

A data index for learning causality.

plaidml

PlaidML is a framework for making deep learning work everywhere.

Nonlincausality

Python package for Granger causality test with nonlinear forecasting methods.

LatentGranger

census

A Python wrapper for the US Census API.

Data-Mining-on-Social-Media

Python scripts to extract tweets and facebook posts from public users.

Neural-GC

Granger causality discovery for neural networks.

sage

For calculating global feature importance using Shapley values.

annotated_deep_learning_paper_implementations

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Time-Series-ARIMA-XGBOOST-RNN

Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN

LSTM-Neural-Network-for-Time-Series-Prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting