JuliaTrustworthyAI/LaplaceRedux.jl

Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.

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aleximmer/Laplace

Laplace approximations for Deep Learning.

Language: Python - Size: 46.3 MB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 499 - Forks: 77

fehiepsi/rethinking-numpyro

Statistical Rethinking (2nd ed.) with NumPyro

Language: Jupyter Notebook - Size: 160 MB - Last synced at: 17 days ago - Pushed at: about 1 year ago - Stars: 455 - Forks: 75

MaximeRobeyns/bayesian_lora

Bayesian Low-Rank Adaptation for Large Language Models

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wiseodd/lapeft-bayesopt

Discrete Bayesian optimization with LLMs, PEFT finetuning methods, and the Laplace approximation.

Language: Python - Size: 4.85 MB - Last synced at: 8 days ago - Pushed at: 9 months ago - Stars: 17 - Forks: 2

JohannesBuchner/snowline

Fit and compare complex models quickly. Laplace Approximation, Variational Bayes, Importance Sampling.

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heal-research/HEAL.NonlinearRegression

Fit and evaluate nonlinear regression models.

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AaltoML/sfr-experiments

Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"

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harrisonpim/uncertainty

🤔 Methods for measuring and visualising the uncertainty in neural networks

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mspronesti/advanced-statistical-inference

Notebooks for Advanced Statistical Inference(ASI) course at EURECOM

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AaltoML/sfr

PyTorch implementation of Sparse Function-space Representation of Neural Networks

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DLR-RM/curvature

Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.

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Madhav-Kanda/AutoDiff-Inference

AutoDiff-Inference: Automatic Differentiation Inference. This Repository combines ADVI's change of variable power with Laplace Approximation to provide better inference for constrained parameters. Work done as a part of development of Bijax

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Sheev13/bayesian-inference

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jkbest2/LaplaceApproximations.jl

Approximate integrals through second-order Taylor expansions

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CCBeard/LApprox

Lightweight package for utilizing the Laplace Approximation to compare Bayesian models

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cplou99/BayesianDL

We provide two notebooks that enable users to explore and experiment with some BDL techniques as Ensembles, MC Dropout and Laplace Approximation. In this way, they allow you to intuitively visualize the main differences among them in a Simulated Dataset and Boston Dataset.

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thudzj/ELLA

Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')

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lorenzofavaro/nlp-ner-tagging

Implementation of a NER Tagging algorithm with Hidden Markov Model.

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tallamjr/bap-numpyro

Bayesian Analysis in Python (2nd ed.) with Numpyro

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MauroCE/Dissertation

Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression

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4ment/laplus

Laplace approximation of the marginal likelihood

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MauroCE/LogisticRegression

Base R Implementation of Logistic Regression from Scratch with Regularization, Laplace Approximation and more

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