Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
-
Updated
Apr 24, 2024 - Python
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
Easy generative modeling in PyTorch
[CVPR'18] ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
Neural Relation Understanding: neural cardinality estimators for tabular data
Code for 'Solving Statistical Mechanics using Variational Autoregressive Networks'.
[AAAI 2024] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
Solving Quantum Statistical Mechanics with Variational Autoregressive Networks and Quantum Circuits
Tensorflow 2.0 implementation of Deep Autoregressive Models
Code for 'From Tensor Network Quantum States to Tensorial Recurrent Neural Networks'.
[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)
AutoregressModel-AE_VAD_CVPR2019 (code reimplemetation)
Variational Autoregressive Network in Julia
Tensorflow 2 implementation of PixelCNN++.
Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.
A enhanced Open Dialogue Context Generator supported by General Language Model Pretraining with Autoregressive Blank Infilling
Solutions for UCBerkeley CS294-158: Deep Unsupervised Learning Spring 2019
Code for variable skipping ICML 2020 paper
A repository for autoregressive prediction via LSTM or some other ANN.
Add a description, image, and links to the autoregressive-neural-networks topic page so that developers can more easily learn about it.
To associate your repository with the autoregressive-neural-networks topic, visit your repo's landing page and select "manage topics."