Statistical Rethinking (2nd ed.) with NumPyro
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Updated
Feb 16, 2024 - Jupyter Notebook
Statistical Rethinking (2nd ed.) with NumPyro
Laplace approximations for Deep Learning.
Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.
Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')
Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.
Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression
Fit and compare complex models quickly. Laplace Approximation, Variational Bayes, Importance Sampling.
Bayesian Low-Rank Adaptation for Large Language Models
Notebooks for Advanced Statistical Inference(ASI) course at EURECOM
Discrete Bayesian optimization with LLMs, PEFT finetuning methods, and the Laplace approximation.
Base R Implementation of Logistic Regression from Scratch with Regularization, Laplace Approximation and more
🤔 Methods for measuring and visualising the uncertainty in neural networks
Lightweight package for utilizing the Laplace Approximation to compare Bayesian models
Fit and evaluate nonlinear regression models.
Approximate integrals through second-order Taylor expansions
Laplace approximation of the marginal likelihood
Implementation of a NER Tagging algorithm with Hidden Markov Model.
PyTorch implementation of Sparse Function-space Representation of Neural Networks
Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"
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