maxim5 / hyper-engine
Python library for Bayesian hyper-parameters optimization
☆89Updated 6 years ago
Alternatives and similar repositories for hyper-engine:
Users that are interested in hyper-engine are comparing it to the libraries listed below
- Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.☆57Updated 7 years ago
- Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another c…☆144Updated 2 years ago
- Population Based Training of Neural Network implemented in Keras☆34Updated last year
- Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another c…☆106Updated 6 years ago
- Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates☆115Updated 7 years ago
- A fully decentralized hyperparameter optimization framework☆122Updated 8 months ago
- Neural Architecture Search with Bayesian Optimisation and Optimal Transport☆133Updated 6 years ago
- A scikit-learn compatible implementation of hyperband☆76Updated 5 years ago
- An example of using a discriminator to correct for a difference in the distributions between the training and test data.☆67Updated 8 years ago
- ☆69Updated 4 years ago
- Functional ANOVA☆122Updated last month
- a feature engineering wrapper for sklearn☆51Updated 4 years ago
- Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"☆67Updated 9 months ago
- Batch Renormalization algorithm implementation in Keras☆98Updated 6 years ago
- Multi-GPU data-parallel training in Keras☆77Updated 7 years ago
- Population Based Training (in PyTorch with sqlite3). Status: Unsupported☆166Updated 7 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆125Updated 5 years ago
- Fuzzy machine learning algorithms implementing the scikit-learn interface.☆75Updated 8 months ago
- Hyperparameter optimization for neural networks☆47Updated 11 years ago
- Better, faster hyper-parameter optimization☆113Updated last year
- ☆74Updated 6 years ago
- simple python interface to SMAC.☆21Updated 6 years ago
- Running parametric t-SNE by Laurens Van Der Maaten with Octave and oct2py.☆266Updated 5 years ago
- Implementing Bayes by Backprop☆183Updated 5 years ago
- Bayesian Weight Uncertainty Dense Layer for Keras☆48Updated 8 years ago
- A general, modular, and programmable architecture search framework☆122Updated last year
- Experimental Gradient Boosting Machines in Python with numba.☆183Updated 6 years ago
- Tools for loading standard data sets in machine learning☆203Updated 2 years ago
- ☆80Updated 6 years ago
- TensorFlow implementation of COCOB☆95Updated last year