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Jan 28, 2020 - Python
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autoregressive
Here are 32 public repositories matching this topic...
Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"
tutorial
course
deep-learning
neural-network
mooc
tensorflow
word2vec
gan
dcgan
pixelcnn
vae
glove
wavenet
magenta
autoregressive
celeba
conditional
vae-gan
cyclegan
nsynth
End-2-end speech synthesis with recurrent neural networks
text-to-speech
neural-network
speech
character
lstm
synthesis
autoregressive
neural
phoneme
long-short-term-memory
mel-spectrogram
end-2-end
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May 7, 2020 - Python
PyTorch implementation of "Conditional Image Generation with PixelCNN Decoders" by van den Oord et al. 2016
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Dec 3, 2017 - Jupyter Notebook
ajdapretnar
commented
Nov 23, 2017
Issue
This is so annoying, I can't stand it anymore.
On OSX, when selecting an attribute to display in a Line Chart, selection doesn't stop with a click. So when I move my mouse around, it is selecting all other attributes I happen to pass with the cursor. Extremely problematic for larger files (things get stuck).
Does not happen on Windows, so I reckon it's a Mac thing.
Expected b
A framework based on Tensorflow for running variational Monte-Carlo simulations of quantum many-body systems.
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Jun 21, 2020 - Python
Forecasting Monthly Sales of French Champagne - Perrin Freres
arma
autoregressive
forecasting-models
time-series-analysis
sarimax
moving-average
arima-model
exponential-smoothing
trend-analysis
seasonality
holt
holtwinters
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Jun 23, 2019 - Jupyter Notebook
Simulate stochastic timeseries that follow ARFIMA, ARMA, ARIMA, AR, etc. processes
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Jun 15, 2020 - Julia
Open
Add distributions
guilhermebodin
commented
Feb 18, 2020
- Exponential #74
- Skellam
- Student t #88
- Location scale student t #87
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Skew t studentNot possible in Distributions.jl -
CauchySince it mean and variance are undefined it needs more tests - Chi #80
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Skew NormalNot possible in Distributions.jl - Negative Binomial
- Chi squared #78
- LogitNormal #77
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Pytorch implementations of autoregressive pixel models - PixelCNN, PixelCNN++, PixelSNAIL
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Dec 13, 2019 - Python
Light, modular framework for dynamic time series modeling, compatible with scikit-learn
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Mar 21, 2020 - Python
InfoMax-VAE pytorch implementation
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May 5, 2020 - Python
R package to estimate time-varying coefficient regressions
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Apr 21, 2020 - R
Implementing Bayes by Backprop with PyTorch. Applied on time-series prediction.
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Dec 12, 2019 - Python
List of papers and code for relevant Generative Models
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Feb 6, 2019 - Jupyter Notebook
Auto Regressive Models applied on Paris Subway Stations. Time Series Analysis. Predictions of affluence.
time-series
models
prediction
forecasting
subway
paris
autoregressive
autoregressive-moving-average
affluence
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Jun 6, 2019 - Jupyter Notebook
Statistics and Forecasting for the Coronavirus disease (COVID-19) in the European Union
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May 24, 2020 - Jupyter Notebook
This repository contains several smaller projects and tutorials that I've created for fun about time series analysis in R.
r
time-series
forecasting
rmd
arima
autoregressive
seasonal-adjustment
time-series-analysis
time-series-forecast
time-series-prediction
time-series-models
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Jul 17, 2018 - HTML
Statistical Learning Models for Damage Detection in Civil Structures.
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Apr 18, 2020 - Jupyter Notebook
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.
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May 8, 2020 - Jupyter Notebook
Personal Website
css
html
markdown
r
statistics
markov-chain
autoregressive
shinyapps
garch
analytical-chemistry
visulization
arsenic
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Jun 17, 2020 - HTML
Companion repo to my work done for the course Tensorflow 2.0: Deep Learning and Artificial Intelligence taught by The Lazy programmer
natural-language-processing
reinforcement-learning
linear-regression
parallel-computing
cnn
generative-adversarial-network
stock-price-prediction
logistic-regression
recommender-system
transfer-learning
ann
autoregressive
rnn-tensorflow
cifar10
tensorflow-serving
fashion-mnist
tflite
tensorflow2
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Mar 24, 2020 - Python
Need to predict how many passengers are going to opt for the airline base on the historical information provided by the Airlines. Using various Time series techniques predicted the number of passengers
timeseries
autoregressive
sarimax
simple-exponential-smoothing
arima-forecasting
holt
sarima
holt-winters-forecasting
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May 3, 2020 - Jupyter Notebook
SolarCloud: Forecasting Photovoltaic Production
nonlinear
prediction
statistical-analysis
neural-networks
feedforward-neural-network
predictive-modeling
arima
autoregressive
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Jan 27, 2017
Tutorial on VAR models + regularization
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Aug 8, 2018 - HTML
Proof of concept for online hybrid message passing inference for AR-HGF.
factor-graphs
autoregressive
message-passing
hierarchical-models
online-learning-algorithms
time-varying
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Jan 17, 2020 - Jupyter Notebook
A tutorial to time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA etc.
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Mar 30, 2020 - Jupyter Notebook
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.
finance
linear-regression
pca-analysis
autoencoders
autoregressive
sp500
autoregressive-moving-average
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Jan 18, 2020 - HTML
A general understanding of Statistics Basics, Different tests with Different Python Libraries
linear-regression
regression
autocorrelation
autoregressive
hypothesis-testing
statsmodels
moving-average
non-stationary
stationarity
kurtosis
robust-linear-regression
diagnostic-plots
homoscedastic
pacf
anova-test
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Jun 25, 2020 - Jupyter Notebook
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PyAF has a API call lEngine.standardPlots(). It gives some classical plots (signal against forecast, residues, trends, cycles, AR)
All the plots are generated with matplotlib
Document the plots generated.
The REST service (issue #20 ) also gives the same plots in a png/base64 encoding, to be documented.