Alternatives and similar repositories for evalset

Users that are interested in evalset are comparing it to the libraries listed below

• automl / HPOlib1.5
  ☆69Updated 5 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆115Updated 12 years ago
• GPflow / GPflowOpt
  Bayesian Optimization using GPflow
  ☆272Updated 4 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆245Updated 3 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆270Updated 5 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• sods / paramz
  Parameterization Framework for parameterized model creation and handling.
  ☆49Updated 3 months ago
• automl / fanova
  Functional ANOVA
  ☆124Updated 7 months ago
• automl / RoBO
  RoBO: a Robust Bayesian Optimization framework
  ☆490Updated 6 years ago
• uber / bayesmark
  Benchmark framework to easily compare Bayesian optimization methods on real machine learning tasks
  ☆154Updated 4 years ago
• mwhoffman / pybo
  Python package for modular Bayesian optimization
  ☆137Updated 4 years ago
• QUVA-Lab / COMBO
  ☆50Updated last year
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• sigopt / sigopt-python
  Simple Python interface for the SigOpt API
  ☆71Updated last week
• ili3p / HORD
  Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
  ☆115Updated 8 years ago
• HIPS / firefly-monte-carlo
  Implementation of an algorithm for Markov chain Monte Carlo with data subsampling
  ☆32Updated 9 years ago
• baptistar / BOCS
  Bayesian Optimization of Combinatorial Structures
  ☆97Updated 6 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 8 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆216Updated 6 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated last year
• PMBio / pygp
  A Gaussian process toolbox in python
  ☆42Updated 13 years ago
• automl / BOAH
  BOAH: Bayesian Optimization & Analysis of Hyperparameters
  ☆67Updated 5 years ago
• SheffieldML / notebook
  Collection of jupyter notebooks for demonstrating software.
  ☆169Updated 2 years ago
• kirthevasank / gp-parallel-ts
  Parallelised Thompson Sampling in GPs for Bayesian Optimisation
  ☆36Updated 8 years ago
• skylergrammer / SimulatedAnnealing
  ☆45Updated 4 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• powerscorinne / GLRM
  ☆99Updated 7 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 6 years ago
• jamesrobertlloyd / gpss-research
  Kernel structure discovery research code - likely to be unstable
  ☆193Updated 10 years ago