There are 1 repository under autoregressive topic.
Awesome resources on normalizing flows.
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
Open-AI's DALL-E for large scale training in mesh-tensorflow.
Generative model for sequential recommendation based on Convolution Neural Networks (CNN))
[ICML 2024] This repository includes the official implementation of our paper "Rejuvenating image-GPT as Strong Visual Representation Learners"
[CVPR 2022] Look Outside the Room: Synthesizing A Consistent Long-Term 3D Scene Video from A Single Image
PyTorch implementation of "Conditional Image Generation with PixelCNN Decoders" by van den Oord et al. 2016
:kiwi_fruit: Autoregressive Models in PyTorch.
🍊 :chart_with_upwards_trend: Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data.
Simulate stochastic timeseries that follow ARFIMA, ARMA, ARIMA, AR, etc. processes
Julia package containing utilities intended for Time Series analysis.
PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.
Pytorch implementations of autoregressive pixel models - PixelCNN, PixelCNN++, PixelSNAIL
Battery SoC prediction using a RNN autoregressive architecture implemented with Pytorch
Score-driven models, aka generalized autoregressive score models, in Julia
Space Group Informed Transformer for Crystalline Materials Generation
Implementation of Metaformer, but in an autoregressive manner
InfoMax-VAE pytorch implementation
Forecasting Monthly Sales of French Champagne - Perrin Freres
[3DV 2024] official repo of 3DV paper "RoomDesigner: Encoding Anchor-latents for Style-consistent and Shape-compatible Indoor Scene Generation"
Autoregressive Bayesian linear model
A Repo of Time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA, RNN Keras, Facebook- Prophet etc.
Sequence-to-Sequence Generative Model for Sequential Recommender System
[ICML 2023] Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
Time series predictive model to forecast the airline monthly passenger
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)
My runthrough of karpathy's lectures (with notes), building NN's from scratch, simple autoregressive language models, GPT models and learnt ML techniques.
Noise-conditional score networks for music composition by annealed Langevin dynamics
PyTorch Lightning Implementation of Diffusion, GAN, VAE, Flow models
Crop yield Forecasting on the basis of meteorological predictions using some Time series & ML models
Abstract: The S&P500 is difficult to predict. Multi-factor models provide a useful framework for making returns predictions and for controlling portfolio risk. This paper explores a three-step process in predicting PCA and Autoencoders factors to generate multi-factor models from the S&P500 component securities.