#
bayesian-optimization
Here are 280 public repositories matching this topic...
Open
TimeSeries Split
20
kanchanapadmanabhan
commented
Jun 26, 2018
The problem I want to use auto-sklearn on is a time-series. Can we modify sklearn to include cv with time series?
A Python implementation of global optimization with gaussian processes.
-
Updated
May 1, 2021 - Python
Sequential model-based optimization with a `scipy.optimize` interface
python
machine-learning
binder
optimization
scientific-computing
bayesopt
gradient
bayesian-optimization
hyperparameter
-
Updated
May 12, 2021 - Python
A modular active learning framework for Python
python
machine-learning
scikit-learn
machine-learning-algorithms
machine-learning-library
machine-learning-api
bayesian-optimization
active-learning
active-learning-module
-
Updated
Jun 8, 2021 - Python
Notebooks about Bayesian methods for machine learning
machine-learning
bayesian-methods
gaussian-processes
bayesian-optimization
bayesian-machine-learning
variational-autoencoder
-
Updated
Jan 19, 2021 - Jupyter Notebook
Open
Grid search variant
3
SimonBlanke
commented
Mar 9, 2021
I think it would be useful to have a grid search optimizer in this package. But its implementation would probably be quite different from other ones (sklearn, ...).
The requirements are:
- The grid search has to stop after n_iter instead of searching the entire search space
- The positions should not be precalculated at the beginning of the optimization (i have concerns about memory load).
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
machine-learning
deep-learning
random-forest
optimization
svm
genetic-algorithm
machine-learning-algorithms
hyperparameter-optimization
artificial-neural-networks
grid-search
tuning-parameters
knn
bayesian-optimization
hyperparameter-tuning
random-search
particle-swarm-optimization
hpo
python-examples
python-samples
hyperband
-
Updated
Jun 4, 2021 - Jupyter Notebook
Sequential Model-based Algorithm Configuration
configuration
hyperparameter-optimization
bayesian-optimization
hyperparameter-tuning
automl
automated-machine-learning
hyperparameter-search
bayesian-optimisation
algorithm-configuration
-
Updated
Apr 12, 2021 - Python
a distributed Hyperband implementation on Steroids
hyperparameter-optimization
bayesian-optimization
automl
automated-machine-learning
neural-architecture-search
-
Updated
Jan 31, 2021 - Python
Experimental Global Optimization Algorithm
optimization
hyperparameter-optimization
global-optimization
bayesian-optimization
blackbox-optimization
-
Updated
Jan 29, 2018 - Python
A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
python
machine-learning
emulation
decision-making
uncertainty-quantification
sensitivity-analysis
bayesian-optimization
experimental-design
bayesian-quadrature
multi-fidelity
-
Updated
Jun 9, 2021 - Python
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
machine-learning
deep-learning
keras
hyperparameter-optimization
machine-learning-library
bayesian-optimization
hyperparameter-tuning
hyperparameter-search
hyperparameter-grid
-
Updated
Oct 18, 2020 - JavaScript
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
-
Updated
Jun 7, 2021 - Python
A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.
python
metadata
data-science
machine-learning
deep-learning
optimization
scikit-learn
parallel-computing
keras
pytorch
artificial-intelligence
xgboost
hyperparameter-optimization
feature-engineering
bayesian-optimization
automated-machine-learning
parameter-tuning
neural-architecture-search
meta-learning
meta-heuristics
-
Updated
Jun 9, 2021 - Python
Bayesian Optimization using GPflow
-
Updated
Dec 2, 2020 - Python
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
machine-learning
optimization
hyperparameter-optimization
bayesian
gaussian-processes
bayesian-optimization
-
Updated
Feb 4, 2020 - C++
Anomaly detection for temporal data using LSTMs
deep-learning
time-series
recurrent-neural-networks
lstm
neural-networks
bayesian-optimization
lstm-neural-networks
anomaly-detection
-
Updated
Nov 27, 2018 - Jupyter Notebook
A hyperparameter optimization framework, inspired by Optuna.
-
Updated
Apr 23, 2021 - Go
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
natural-language-processing
hyperparameter-optimization
topic-modeling
bayesian-optimization
hyperparameter-tuning
latent-dirichlet-allocation
evaluation-metrics
neural-topic-models
latent-semantic-analysis
topic-models
hyperparameter-search
non-negative-matrix-factorization
-
Updated
Jun 9, 2021 - Python
Toolbox for Bayesian Optimization and Model-Based Optimization in R
r
optimization
hyperparameter-optimization
r-package
mlr
model-based-optimization
black-box-optimization
bayesian-optimization
mlrmbo
-
Updated
Jun 10, 2021 - R
A lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)
-
Updated
Apr 19, 2021 - C++
Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB
matlab
bayesian-optimization
optimization-algorithms
log-likelihood
noiseless-functions
noisy-functions
-
Updated
Apr 20, 2021 - MATLAB
Surrogate Optimization Toolbox for Python
asynchronous
optimization
global-optimization
black-box-optimization
gaussian-processes
bayesian-optimization
radial-basis-function
global-optimization-algorithms
surrogate-models
surrogate-based-optimization
-
Updated
Feb 3, 2021 - Jupyter Notebook
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
-
Updated
Jan 28, 2019 - Python
A toolset for black-box hyperparameter optimisation.
-
Updated
Jan 26, 2020 - Python
BOPP: Bayesian Optimization for Probabilistic Programs
-
Updated
Nov 9, 2017 - Clojure
A fully decentralized hyperparameter optimization framework
optimization
parallelism
hyperparameter-optimization
bayesian-optimization
cmaes
conditional-search-space
-
Updated
Sep 30, 2020 - Python
GPstuff - Gaussian process models for Bayesian analysis
regression
octave
classification
survival-analysis
bayesian
spatial-analysis
bayesian-inference
expectation-propagation
mcmc
gaussian-processes
variational-inference
bayesian-optimization
covariance-functions
-
Updated
Aug 5, 2020 - MATLAB
Parallel Hyperparameter Optimization in Python
machine-learning
neural-network
parallel-computing
neural-networks
hyperparameter-optimization
tuning-parameters
gaussian-processes
bayesian-optimization
hyperparameter-tuning
cluster-deployment
sklearn-compatible
kubernetes-deployment
tensorflow-examples
blackbox-optimization
production-system
keras-examples
scipy-compatible
pytorch-compatible
-
Updated
Jun 3, 2021 - Jupyter Notebook
Improve this page
Add a description, image, and links to the bayesian-optimization topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the bayesian-optimization topic, visit your repo's landing page and select "manage topics."
I'm using mxnet to do some work, but there is nothing when I search the mxnet trial and example.