Machine Learning
7 posts
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Building Non-Standard Regression Models with JAX
Using JAX's automatic differentiation to train a Zero-Inflated Generalised Poisson regression model
- jax
- regression
- count-data
- ZIP
- poisson
- maximum-likelihood
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Online Bayesian Learning Part 4: Non-stationary data and R-VGA
Adapting R-VGA to work in non-stationary environments.
- bayesian
- neural-networks
- r-vga
- non-stationary
- adaptive-learning
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Online Bayesian Learning Part 3: R-VGA
Deriving and implementing the R-VGA algorithm for online learning with neural networks on streaming binary classification data
- bayesian
- neural-networks
- variational-inference
- jax
- equinox
- online
- r-vga
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Online Bayesian Learning Part 2: Bayesian Neural Networks With Variational Inference
A quick detour to introduce variational inference and use it to train a small Bayesian neural network with jax/eqx
- bayesian
- neural-networks
- variational-inference
- jax
- equinox
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Online Bayesian Learning Part 1: Exact recursive inference
Part 1 of a series of posts looking into the problem of 'online' learning using Bayesian methods
- bayesian
- neural-networks
- variational-inference
- jax
- equinox
- online
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Huber Regression
Robust regression using Huber loss function. Handle outliers and improve model stability with robust statistical methods.
- regression
- robust-statistics
- huber
- machine-learning
- python
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Quantile Regression
Quantile regression for uncertainty estimation beyond the mean. PyTorch implementation for predicting conditional quantiles.
- quantile
- regression
- statistics
- machine-learning
- pytorch