179 Open source projects that are alternatives of or similar to bayex

Generalized and Efficient Blackbox Optimization System.

Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution

PIX is an image processing library in JAX, for JAX.

pyrff: Python implementation of random fourier feature approximations for gaussian processes

A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations

Method of Manufactured Solutions Repository

Statically sized tensors and related operations for Julia

Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much, much more.

Fitness landscape exploration sandbox for biological sequence design.

Reverse Mode Automatic Differentiation for Julia

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.

Toy implementations of some popular ML optimizers using Python/JAX

Local, global, and beyond optimization for scientific machine learning (SciML)

ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives (Deep RL Workshop 2021)

A julia package for Taylor polynomial expansions in one and several independent variables.

Federated posterior averaging implemented in JAX

Julia port of the Python autograd package.

Bayesian Optimization algorithms with various recent improvements

Automatic Differentiation Library for Computational and Mathematical Engineering

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Source Code Generation for Automatic Differentiation using Operator Overloading

Repository for B0M36SPJ

Algorithms that combine tensor network methods with automatic differentiation

Standard basic quantum circuit simulator building blocks. (archived, for it is moved to Yao.jl)

Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.

Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.

Differentiable interface to FEniCS for JAX using dolfin-adjoint/pyadjoint

Yes, it's a camel case.

Intimate Affection Auditor

A GPT, made only of MLPs, in Jax

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.

Gaussian processes and Bayesian optimization for images and hyperspectral data

A simple library for creating complex neural networks

A concise C++17 implementation of automatic differentiation (operator overloading)

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

Automatic Differentiation for Tensor Algebras

Forward Mode Automatic Differentiation for Julia

Differentiable molecular simulation of proteins with a coarse-grained potential

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

Deodorant: Solving the problems of Bayesian Optimization

Gorgonia is a library that helps facilitate machine learning in Go.

Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.

『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)

Hyperparameter optimization in Julia.

Tensorlang, a differentiable programming language based on TensorFlow

Revisiting Rainbow

Tensors and differentiable operations (like TensorFlow) in Rust

Surrogate Final BH properties

Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"

Unofficial JAX implementations of deep learning research papers

Differential Algebra Computational Toolbox

👩 Pytorch and Jax code for the Madam optimiser.

Computational Fluid Dynamics in JAX

Numerically solves equations of motion for a given Hamiltonian function

Python library for Bayesian hyper-parameters optimization

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

Automatic Differentiation using Pseudo Lenses. Neat.

A Python library for machine-learning and feedback loops on streaming data

JAX implementations of core Deep RL algorithms