Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
GPL-3.0 License
Scalable and user friendly neural forecasting algorithms.
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
A Python package for Bayesian forecasting with object-oriented design and probabilistic models un...
TorchCFM: a Conditional Flow Matching library
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
A state-of-the-art Video Frame Interpolation Method using feature flows blending. (CVPR 2020)
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noi...
Probabilistic time series modeling in Python
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series F...
A Python package for building Bayesian models with TensorFlow or PyTorch
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art D...
NeuralProphet: A simple forecasting package
Benchmark time series data sets for PyTorch
Implementation of DeepMind's Deep Generative Model of Radar (DGMR) https://arxiv.org/abs/2104.00954
List of papers, code and experiments using deep learning for time series forecasting