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bayesian-optimization
Here are 216 public repositories matching this topic...
1
mfeurer
commented
Feb 4, 2019
with the Power Transformer.
A Python implementation of global optimization with gaussian processes.
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Updated
Oct 1, 2020 - Python
Sequential model-based optimization with a `scipy.optimize` interface
python
machine-learning
binder
optimization
scientific-computing
bayesopt
gradient
bayesian-optimization
hyperparameter
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Updated
Sep 29, 2020 - Python
Notebooks about Bayesian methods for machine learning
machine-learning
bayesian-methods
gaussian-processes
bayesian-optimization
bayesian-machine-learning
variational-autoencoder
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Updated
Oct 7, 2020 - Jupyter Notebook
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
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Sep 29, 2020 - Python
Sequential Model-based Algorithm Configuration
configuration
hyperparameter-optimization
bayesian-optimization
hyperparameter-tuning
automl
automated-machine-learning
hyperparameter-search
bayesian-optimisation
algorithm-configuration
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Oct 7, 2020 - Python
Experimental Global Optimization Algorithm
optimization
hyperparameter-optimization
global-optimization
bayesian-optimization
blackbox-optimization
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Jan 29, 2018 - Python
a distributed Hyperband implementation on Steroids
hyperparameter-optimization
bayesian-optimization
automl
automated-machine-learning
neural-architecture-search
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Sep 6, 2020 - 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
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Updated
Oct 6, 2020 - 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
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Updated
Sep 25, 2020 - JavaScript
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
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Aug 30, 2020 - Jupyter Notebook
Bayesian Optimization using GPflow
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Jun 30, 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
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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
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Nov 27, 2018 - Jupyter Notebook
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
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Oct 8, 2020 - R
Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB
matlab
bayesian-optimization
optimization-algorithms
log-likelihood
noiseless-functions
noisy-functions
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Updated
Sep 13, 2019 - MATLAB
A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
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Updated
Oct 2, 2020 - Python
c-bata
commented
Apr 21, 2020
A lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)
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Sep 4, 2020 - C++
A toolset for black-box hyperparameter optimisation.
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Updated
Jan 26, 2020 - Python
Neural Architecture Search with Bayesian Optimisation and Optimal Transport
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Updated
Jan 28, 2019 - Python
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
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Jun 23, 2020 - Jupyter Notebook
BOPP: Bayesian Optimization for Probabilistic Programs
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Updated
Nov 9, 2017 - Clojure
A fully decentralized hyperparameter optimization framework
optimization
parallelism
hyperparameter-optimization
bayesian-optimization
cmaes
conditional-search-space
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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
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Updated
Aug 5, 2020 - MATLAB
Python library for Bayesian hyper-parameters optimization
python
data-science
machine-learning
big-data
deep-learning
neural-network
tensorflow
model-selection
hyperparameter-optimization
convolutional-neural-networks
gaussian-processes
bayesian-optimization
random-search
optimization-algorithms
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Updated
Aug 28, 2018 - Python
Hyperparameter optimization in Julia.
optimization
hyperparameter-optimization
global-optimization
bayesian-optimization
parameter-tuning
random-sampling
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Aug 12, 2020 - Julia
Benchmark framework to easily compare Bayesian optimization methods on real machine learning tasks
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Updated
Sep 10, 2020 - Python
Phoenics: Bayesian optimization for efficient experiment planning
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Updated
Jul 3, 2019 - Python
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What would you like to be added: As title
Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.
**Without this feature, how does current nni