Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)
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Updated
May 14, 2018 - Python
Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)
One Algorithm, Two Models, and a Prediction
Generative Predictive Networks — an experimental attempt to stabilize GANs' training.
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
Brain Graph Super-Resolution: how to generate high-resolution graphs from low-resolution graphs? (Python3 version)
ABMT (Adversarial Brain Multiplex Translator) for brain graph translation using geometric generative adversarial network (gGAN).
Graph SuperResolution Network using geometric deep learning.
A few-shot learning approach to forecasting the evolution of the brain connectome.
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.
Simple prolog application that uses predicate logic to diagnose diseases.
Predicting multigraph brain population from a single graph
Federated time-dependent graph evolution prediction with missing timepoints.
MultiGraphGAN for predicting multiple target graphs from a source graph using geometric deep learning.
PredRNN implementation using Tensorflow.
Our group project for Govhack2023
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
Analysis code for the OpenScope Credit Assignment project.
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
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