Kaggle Kore 2022 - An autoregressive modeling approach to imitation learning
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Updated
Dec 24, 2022 - Python
Kaggle Kore 2022 - An autoregressive modeling approach to imitation learning
Official code for "Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving", ICML 2021
Análise da série histórica Dados Históricos Petrobras Ações Ordinárias - PETR3_SA 2020-10-07 00:00:00 até 2023-10-06 00:00:00
Time Series Analysis Projects
I investigate the Asymmetric Volatility Spillover Effects within and across six major International stock markets. United States, Canada, France, Germany, Italy & Japan
Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.
Time series modeling of US real estate housing prices
Autoregressive modelling for time-series used from Andrej Karpathy shakespeare data
Code repository for "Machine Learning Predictors for Min-Entropy Estimation" (arXiv:2406.19983). Implements RCNN and GPT-2 models for entropy prediction in RNGs, with data generation, training pipelines, and analysis scripts.
Forecast of Salado River level (Santa Fe, Arg.)
Time-series forecasting tecniques applied to the stock market
Forecasting eletric load using autoregressive recurrent networks (tensorflow)
PyTorch implementation for "Long Horizon Temperature Scaling", ICML 2023
Repository containing a gif of the evolution of a Functional Autoregressive Process of order one, namley a FAR(1) model.
mVARbox is a Matlab toolbox for uni/multivariate data series analysis in both time/space and frequency domains, with focus on mutivariate autoregressive (VAR) models
Signals Modeling using Autoregressive Model
Time Series based Ensemble Model Output Statistics
Music generation with machine learning: Completing Bach's unfinished Contrapunctus XIV. A variety of models including linear regression, multilayer perceptrons and echo state networks are used as autoregressive models to take on the challenging time-series task.
Machine Learning projects
Using Python to visualize COVID-19 trends with machine learning. Modelled in JupyterLab using the fbProphet library to construct time series forecasts.
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