Scalable and user friendly neural :brain: forecasting algorithms.

Time Series Analysis with Python Cookbook, Second Edition - Published by Packt

Time Series Prediction: A Non Linear Approach with Neural Networks

Bindings for Nixtla's neuralforecast Library in R, specifically KANs, to use with {modeltime} package. Nixtla's KAN is called from R via {reticulate}, which is then ported into {parsnip} and bridged to {modeltime}.

how to use nixtla's neuralforecast (SOTA DL) python package via R.

Nixtla time series forecasting plugins for Claude Code. StatsForecast, MLForecast, and NeuralForecast integrations with agent skills.

I conducted an experiment following the ideas of Nie et al. (2003) https://arxiv.org/pdf/2211.14730.pdf However, I changed their setting, using NeuralForecast for predictions on the Exchange dataset, which represents exchange rates of 7 different countries' currencies from 1990 to 2010. I extended the benchmark over other models.

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Informer Forecaster for the Forecasting problem category as per Ready Tensor specifications.

NHiTS Forecaster for the Forecasting problem category as per Ready Tensor specifications.

This project explores the performance of modern deep learning architectures for time series forecasting using the NeuralForecast framework — an open-source library built on top of PyTorch, designed to simplify training and evaluation of state-of-the-art forecasting models.

This project uses NeuralForecast and KAN (Kernel-based Attention Networks) to forecast battery discharge cycles. It processes raw battery data, aggregates capacity per cycle, and trains a model to predict future battery performance. The model is evaluated using metrics like MAE and MSE for prediction accuracy.

A conda-smithy repository for neuralforecast.

simple neuralforecast

use neuralforecast package

This activity employed a dataset with highly imbalanced data and tested a library that utilizes Time Series LLMs in an attempt to develop a model capable of achieving acceptable, rather than optimal, performance.

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repository to experiment with neuralforecast library to predict glucose

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Neural 🧠 models for time series forecasting

Tutorial on time series forecasting with NeuralForecast to be released in LightningAI

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UCSD Neural Forecasting SMASH Hackathon

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Minimal reference implementation for running Lightning and NeuralForecast on Intel GPU via native PyTorch XPU.

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Stock's price is predicted by TFT of neuralforecast.