Papers with Code 아카이브

Bayesian Optimization

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tsudalab/PrefInt

Leveraging Legacy Data to Accelerate Materials Design via Preference Learning

https://github.com/tuvalusoftware/AutomatedMarketplaces

Combinatorial 3D Shape Generation via Sequential Assembly

https://github.com/uoguelph-mlrg/GenerativeLEGO

Combinatorial 3D Shape Generation via Sequential Assembly

https://github.com/vanderschaarlab/autoprognosis

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning

https://github.com/vanderschaarlab/llambo

Large Language Models to Enhance Bayesian Optimization

https://github.com/weepingwillowben/hyperparam-opt

Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters

https://github.com/willieneis/gp-martingales

Uncertainty quantification using martingales for misspecified Gaussian processes

https://github.com/wujian16/qKG

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

https://github.com/xingchenwan/nasbowl

Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels

https://github.com/xkp793003821/autokeras_cooper

Auto-Keras: An Efficient Neural Architecture Search System

https://github.com/yanpei18345156216/BayesianOptimization

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/yerevann/chemlactica

Genetic-guided GFlowNets for Sample Efficient Molecular Optimization

https://github.com/yiwang89/fmfn-BayesianOptimization

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/yiyuezhuo/A-Tutorial-on-Bayesian-Optimization-exmaple

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/yoomambo/BayesianOptimization_Tuned

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/ytopt-team/ytopt-libensemble

Autotuning Apache TVM-based Scientific Applications Using Bayesian Optimization

https://github.com/yunyishen/mssl

Integrals over Gaussians under Linear Domain Constraints

https://github.com/zatang007/BayesianOptimization

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/zhaoolee/garss

Probabilistic Artificial Intelligence

https://github.com/zi-w/Ensemble-Bayesian-Optimization

Batched Large-scale Bayesian Optimization in High-dimensional Spaces

https://github.com/zygmuntz/hyperband

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.