sobanbabubiitk Goto Github PK

alebo

Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization

bayesian-machine-learning

Notebooks about Bayesian methods for machine learning

bo_pr

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

bode

Bayesian Optimal Design of Experiments

contextualbo

Code associated with paper "High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization"

cornell-moe

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

data-driven-high-dimensional-uq-analysis

Project source code and data for uncertainty quantification on combustion instability prediction using a machine-learning-enhanced strategy

dgemo

[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations

explainable-uq-analysis

Project source code and data for explainable machine-learning-based dimensionality reduction for fast uncertainty quantification.

forward_uq

A step-by-step tutorial to perform forward uncertainty quantification analysis using Monte Carlo method

gaussian-process

Implementing a Gaussian Process regression model from scratch

gaussianprocesses

Modern Gaussian Processes: Scalable Inference and Novel Applications

gitignore

A collection of useful .gitignore templates

irt-leaderboard

Leaderboards are widely used in NLP and push the field forward.

machine_learning_basics

Plain python implementations of basic machine learning algorithms

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

morbo

Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces

multi-fidelity-ml

Project source code and data for multi-fidelity machine learning strategy for flame model identification

multiobjective_bayesian_qhvi

nevergrad

A Python toolbox for performing gradient-free optimization

preference-exploration

Code for replicating experiments from the paper, Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes, published in AISTATS 2022.

pydes

Multi-objective Stochastic Bayesian Optimization with Quantified Uncertainties on the Pareto Frontier

pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

robust_mobo

Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"

ubuntu

My emacs files