Generative Predictive Networks — an experimental attempt to stabilize GANs' training.
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Updated
Apr 20, 2019 - Python
Generative Predictive Networks — an experimental attempt to stabilize GANs' training.
One Algorithm, Two Models, and a Prediction
PredRNN implementation using Tensorflow.
Simple prolog application that uses predicate logic to diagnose diseases.
Graph SuperResolution Network using geometric deep learning.
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.
Predicting multigraph brain population from a single graph
A few-shot learning approach to forecasting the evolution of the brain connectome.
Our group project for Govhack2023
Brain Graph Super-Resolution: how to generate high-resolution graphs from low-resolution graphs? (Python3 version)
Analysis code for the OpenScope Credit Assignment project.
Federated time-dependent graph evolution prediction with missing timepoints.
ABMT (Adversarial Brain Multiplex Translator) for brain graph translation using geometric generative adversarial network (gGAN).
Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)
MultiGraphGAN for predicting multiple target graphs from a source graph using geometric deep learning.
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
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