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

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.

EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax

Contains code for the paper "Vision Transformers are Robust Learners" (AAAI 2022).

JAX-based Spiking Neural Network framework

Learnable Embedding Space for Efficient Neural Architecture Compression

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

Mixed-Integer Parallel Efficient Global Optimization

A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.

Fortran compilers, preprocessors, static analyzers, transpilers, IDEs, build systems, etc.

Chef Transformer 🍲 .

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Factor graphs and nonlinear optimization for JAX

Elastic Full Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

PHYSBO -- optimization tools for PHYsics based on Bayesian Optimization

Functional models and algorithms for sparse signal processing

A didactic Gaussian process package for researchers in Jax.

Abstract operators for large scale optimization in Julia

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022

Bayesian Optimization and Grid Search for xgboost/lightgbm

XCFun: A library of exchange-correlation functionals with arbitrary-order derivatives

Automatic Differentiation for R

Parallel Hyperparameter Tuning in Python

KoCLIP: Korean port of OpenAI CLIP, in Flax

Causing: CAUsal INterpretation using Graphs

Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.

A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations

Tutorial on Bayesian optimization in R

A numerical optimisation and deep learning framework for D.

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

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

Statically sized tensors and related operations for Julia

Fitness landscape exploration sandbox for biological sequence design.

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

Toy implementations of some popular ML optimizers using Python/JAX

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

Federated posterior averaging implemented in JAX

Bayesian Optimization algorithms with various recent improvements

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

Repository for B0M36SPJ

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

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

Yes, it's a camel case.

A GPT, made only of MLPs, in Jax

Gaussian processes and Bayesian optimization for images and hyperspectral data

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

Automatic Differentiation for Tensor Algebras

Differentiable molecular simulation of proteins with a coarse-grained potential

Deodorant: Solving the problems of Bayesian Optimization

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

Hyperparameter optimization in Julia.

Revisiting Rainbow

Surrogate Final BH properties

Unofficial JAX implementations of deep learning research papers

👩 Pytorch and Jax code for the Madam optimiser.

Computational Fluid Dynamics in JAX

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

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.