BluePyOpt

Model optimization framework

A flexible framework for optimizing model parameters in computational neuroscience and related fields.

Blue Brain Python Optimisation Library

GitHub

200 stars
18 watching
98 forks
Language: Python
last commit: 20 days ago
Linked from 1 awesome list

biological-simulationscomputational-neurosciencecross-platformelectrophysiologyevolutionary-algorithmsgenetic-algorithmmodellingneuronsneuroscienceoptimisationsparameterpython

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
brainpy/brainpy A Python framework for flexible and efficient brain dynamics programming and simulation 533
jonfanlab/glonet A software framework for training neural networks to optimize dielectric metasurfaces using physics-driven generative models and global optimization algorithms. 101
fpicetti/occamypy A library for solving large-scale optimization problems with flexible and scalable vector and operator definitions 54
jungtaekkim/bayeso A framework for optimizing hyperparameters in machine learning models using Bayesian optimization 93
100/solid A comprehensive framework for solving optimization problems without gradient calculations. 576
c-bata/goptuna A decentralized hyperparameter optimization framework inspired by Optuna. 260
cbfinn/gps An implementation of guided policy search and LQG-based trajectory optimization for reinforcement learning 598
pyomeca/bioptim An optimization framework for biomechanics and control problems using multiple algorithms and libraries. 93
automl/robo A Bayesian optimization framework designed to optimize complex functions with robustness and flexibility 483
bluebrain/morphio A C++ library for reading and writing neuronal morphology data in various file formats. 27
brml/climin A framework for optimizing machine learning functions using gradient-based optimization methods. 180
ncbi-nlp/bluebert Pre-trained language models for biomedical natural language processing tasks 558
hjmshi/pytorch-lbfgs A PyTorch implementation of L-BFGS optimization algorithm for training neural networks 586
neuralmagic/sparseml Enables the creation of smaller neural network models through efficient pruning and quantization techniques 2,071
alibaba/conv-llava This project presents an optimization technique for large-scale image models to reduce computational requirements while maintaining performance. 104