Investigation into Generative Neural Networks.
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Updated
Nov 2, 2018 - Python
Investigation into Generative Neural Networks.
A TensorFlow implementation of the PixelCNN.
Solutions for UCBerkeley CS294-158: Deep Unsupervised Learning Spring 2019
A repository for autoregressive prediction via LSTM or some other ANN.
Code for variable skipping ICML 2020 paper
AutoregressModel-AE_VAD_CVPR2019 (code reimplemetation)
[CVPR'18] ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans
Prediction of solar energy consumption using recurrent neural networks
Code and scripts for training, testing and sampling auto-regressive recurrent language models on PyTorch with RNN, GRU and LSTM layers
Neural Relation Understanding: neural cardinality estimators for tabular data
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
Tensorflow 2.0 implementation of Deep Autoregressive Models
Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.
Global Autoregressive Models (GAMs) for Data-Efficient Sequence Learning
Variational Autoregressive Network in Julia
predict sales based on time series data explicitely using deep learning
Tensorflow 2 implementation of PixelCNN++.
An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
A enhanced Open Dialogue Context Generator supported by General Language Model Pretraining with Autoregressive Blank Infilling
Machine Learning-based research for UPMC
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