All Projects → Nasbot → Similar Projects or Alternatives

199 Open source projects that are alternatives of or similar to Nasbot

pyrff
pyrff: Python implementation of random fourier feature approximations for gaussian processes
Stars: ✭ 24 (-80%)
Gpstuff
GPstuff - Gaussian process models for Bayesian analysis
Stars: ✭ 106 (-11.67%)
Nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Stars: ✭ 10,698 (+8815%)
ESNAC
Learnable Embedding Space for Efficient Neural Architecture Compression
Stars: ✭ 27 (-77.5%)
Limbo
A lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)
Stars: ✭ 157 (+30.83%)
Pysot
Surrogate Optimization Toolbox for Python
Stars: ✭ 136 (+13.33%)
Bayesian Machine Learning
Notebooks about Bayesian methods for machine learning
Stars: ✭ 1,202 (+901.67%)
syne-tune
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Stars: ✭ 105 (-12.5%)
Hpbandster
a distributed Hyperband implementation on Steroids
Stars: ✭ 456 (+280%)
Hyperactive
A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.
Stars: ✭ 182 (+51.67%)
approxposterior
A Python package for approximate Bayesian inference and optimization using Gaussian processes
Stars: ✭ 36 (-70%)
mindware
An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Stars: ✭ 34 (-71.67%)
Ts Emo
This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).
Stars: ✭ 39 (-67.5%)
Bayesianoptimization
A Python implementation of global optimization with gaussian processes.
Stars: ✭ 5,611 (+4575.83%)
mango
Parallel Hyperparameter Tuning in Python
Stars: ✭ 241 (+100.83%)
Cornell Moe
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
Stars: ✭ 198 (+65%)
GPim
Gaussian processes and Bayesian optimization for images and hyperspectral data
Stars: ✭ 29 (-75.83%)
hyper-engine
Python library for Bayesian hyper-parameters optimization
Stars: ✭ 80 (-33.33%)
Bayeso
Simple, but essential Bayesian optimization package
Stars: ✭ 57 (-52.5%)
Mutual labels:  bayesian-optimization
Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Stars: ✭ 1,357 (+1030.83%)
Mutual labels:  gaussian-processes
Nsganetv2
[ECCV2020] NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search
Stars: ✭ 52 (-56.67%)
Efficientnas
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906
Stars: ✭ 44 (-63.33%)
Deep architect
A general, modular, and programmable architecture search framework
Stars: ✭ 110 (-8.33%)
Safeopt
Safe Bayesian Optimization
Stars: ✭ 90 (-25%)
Mutual labels:  gaussian-processes
Neural Architecture Search With Rl
Minimal Tensorflow implementation of the paper "Neural Architecture Search With Reinforcement Learning" presented at ICLR 2017
Stars: ✭ 37 (-69.17%)
Epinow2
Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
Stars: ✭ 36 (-70%)
Mutual labels:  gaussian-processes
Mtlnas
[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
Stars: ✭ 58 (-51.67%)
Gaussianprocesses
Python3 project applying Gaussian process regression for forecasting stock trends
Stars: ✭ 78 (-35%)
Mutual labels:  gaussian-processes
Morph Net
Fast & Simple Resource-Constrained Learning of Deep Network Structure
Stars: ✭ 937 (+680.83%)
Awesome Architecture Search
A curated list of awesome architecture search resources
Stars: ✭ 1,078 (+798.33%)
Petridishnn
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Stars: ✭ 112 (-6.67%)
Autokeras
AutoML library for deep learning
Stars: ✭ 8,269 (+6790.83%)
Robnets
[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
Stars: ✭ 95 (-20.83%)
Deephyper
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
Stars: ✭ 117 (-2.5%)
Gp Infer Net
Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
Stars: ✭ 37 (-69.17%)
Mutual labels:  gaussian-processes
Hydra
Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.
Stars: ✭ 87 (-27.5%)
Ipynotebook machinelearning
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
Stars: ✭ 27 (-77.5%)
Mutual labels:  gaussian-processes
Numpy Ml
Machine learning, in numpy
Stars: ✭ 11,100 (+9150%)
Mutual labels:  gaussian-processes
La3dm
Learning-aided 3D mapping
Stars: ✭ 77 (-35.83%)
Mutual labels:  gaussian-processes
Devol
Genetic neural architecture search with Keras
Stars: ✭ 925 (+670.83%)
Gradient Free Optimizers
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
Stars: ✭ 711 (+492.5%)
Mutual labels:  bayesian-optimization
Hypertunity
A toolset for black-box hyperparameter optimisation.
Stars: ✭ 119 (-0.83%)
Mutual labels:  bayesian-optimization
Bcpd
Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
Stars: ✭ 116 (-3.33%)
Mutual labels:  gaussian-processes
Slimmable networks
Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019
Stars: ✭ 708 (+490%)
Awesome Automl And Lightweight Models
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
Stars: ✭ 691 (+475.83%)
Paddleslim
PaddleSlim is an open-source library for deep model compression and architecture search.
Stars: ✭ 677 (+464.17%)
Autodl Projects
Automated deep learning algorithms implemented in PyTorch.
Stars: ✭ 1,187 (+889.17%)
Randwirenn
Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
Stars: ✭ 675 (+462.5%)
Awesome Federated Learning
Federated Learning Library: https://fedml.ai
Stars: ✭ 624 (+420%)
Gpflow
Gaussian processes in TensorFlow
Stars: ✭ 1,547 (+1189.17%)
Mutual labels:  gaussian-processes
Modal
A modular active learning framework for Python
Stars: ✭ 1,148 (+856.67%)
Mutual labels:  bayesian-optimization
Auto Sklearn
Automated Machine Learning with scikit-learn
Stars: ✭ 5,916 (+4830%)
Mutual labels:  bayesian-optimization
Pycrop Yield Prediction
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
Stars: ✭ 67 (-44.17%)
Mutual labels:  gaussian-processes
Smac3
Sequential Model-based Algorithm Configuration
Stars: ✭ 564 (+370%)
Mutual labels:  bayesian-optimization
Hyperparameter Optimization Of Machine Learning Algorithms
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
Stars: ✭ 516 (+330%)
Mutual labels:  bayesian-optimization
Bopp
BOPP: Bayesian Optimization for Probabilistic Programs
Stars: ✭ 112 (-6.67%)
Mutual labels:  bayesian-optimization
Graphnas
This directory contains code necessary to run the GraphNAS algorithm.
Stars: ✭ 104 (-13.33%)
Neural Kernel Network
Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
Stars: ✭ 67 (-44.17%)
Mutual labels:  gaussian-processes
Gaussianblur
An easy and fast library to apply gaussian blur filter on any images. 🎩
Stars: ✭ 473 (+294.17%)
Mutual labels:  gaussian-processes
Tenas
[ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang
Stars: ✭ 63 (-47.5%)
1-60 of 199 similar projects