OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

MultiGraphGAN for predicting multiple target graphs from a source graph using geometric deep learning.

Graph SuperResolution Network using geometric deep learning.

Analysis code for the OpenScope Credit Assignment project.

Predicting multigraph brain population from a single graph

A Python toolbox for predicting brain network (graph) evolution over time from a single observation. The codes of the 20 competing Kaggle teams along with the competition datasets are made available.

Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)

ABMT (Adversarial Brain Multiplex Translator) for brain graph translation using geometric generative adversarial network (gGAN).

Brain Graph Super-Resolution: how to generate high-resolution graphs from low-resolution graphs? (Python3 version)

Federated time-dependent graph evolution prediction with missing timepoints.

Our group project for Govhack2023

A few-shot learning approach to forecasting the evolution of the brain connectome.

PredRNN implementation using Tensorflow.

Generative Predictive Networks — an experimental attempt to stabilize GANs' training.

One Algorithm, Two Models, and a Prediction

Simple prolog application that uses predicate logic to diagnose diseases.