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Deep universal probabilistic programming with Python and PyTorch
A community supported Windows build for jax.
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benchmark problems for single and multi-objective black-box optimization
PDF references add-on for Zotero.
Project page for the paper: Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation
Productive, portable, and performant GPU programming in Python.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Balancing Objective Optimization and Constraint Satisfaction in Expensive Constrained Evolutionary Multi-Objective Optimization
🆓免费的 ChatGPT 镜像网站列表，持续更新。List of free ChatGPT mirror sites, continuously updated.
Flax is a neural network library for JAX that is designed for flexibility.
A minimal implementation of Gaussian process regression in PyTorch
Minimal Implementation of Bayesian Optimization in JAX
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
A best practice for deep learning project template architecture.
JAX - A curated list of resources https://github.com/google/jax
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
⚡ A Fast, Extensible Progress Bar for Python and CLI
A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Official electron build of draw.io
A framework for single/multi-objective optimization with metaheuristics