Repository Index

Kronos: A Foundation Model for the Language of Financial Markets

Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

• neocortex
• artificial-intelligence
• machine-intelligence
• hierarchical-temporal-memory

Chronos: Pretrained Models for Time Series Forecasting

• forecasting
• large-language-models
• llm
• machine-learning

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

• time-series-classification
• deep-learning
• fastai
• pytorch

Probabilistic time series modeling in Python

• time-series
• deep-learning
• forecasting
• neural-networks

Technical Analysis Library using Pandas and Numpy

• trading
• technical-analysis
• python3
• volume

Time series forecasting with PyTorch

• pytorch
• forecasting
• gpu
• uncertainty

Lightning ⚡️ fast forecasting with statistical and econometric models.

• time-series
• statistics
• forecasting
• arima

NeuralProphet: A simple forecasting package

• forecasting
• time-series
• machine-learning
• fbprophet

TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

• time-series
• time-series-forecasting
• deep-learning
• forecasting

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

• pytorch
• graph-neural-networks
• temporal-networks
• temporal-graphs

[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"

• cross-modal-learning
• cross-modality
• deep-learning
• language-model

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

• deep-learning
• forecasting
• forecasting-model
• linear-models

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight)

• time-series-forecasting
• transformer

Exponentially Weighted Moving Average algorithms for Go.

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

• time-series-analysis
• model-selection
• bayesian-inference
• anomaly-detection