Stars
Simple class that defines USGS figure specifications for matplotlib
Fit interpretable models. Explain blackbox machine learning.
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
TimeGPT-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 …
Source code for ClimateLearn
Pytorch implementation of NIPS'23 paper: Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
Implementation of the algorithm described in: SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise
😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness
The official code for "One Fits All: Power General Time Series Analysis by Pretrained LM (NeurIPS 2023 Spotlight)"
Color palette package in R inspired by works at the Metropolitan Museum of Art in New York
Color palette package inspired by National Parks
PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Representation learning on large graphs using stochastic graph convolutions.
Code accompanying our NeurIPS 2022 traffic4cast challenge
Code accompanying our NeurIPS 2021 traffic4cast challenge
This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Training: Benchmarking and Rethinking" in PyTorch.
Machine learning metrics for distributed, scalable PyTorch applications.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
High-Performance Symbolic Regression in Python and Julia
Neural network loss functions for regression and classification tasks that can say "I don't know".
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch