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Bayesian Optimization

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

https://github.com/nobuo-namura/regional-expected-improvement

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Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization

https://github.com/noemiejaquier/materngabo

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Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels

https://github.com/novonordisk-research/BEE-BO

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Batched Energy-Entropy acquisition for Bayesian Optimization

https://github.com/nphdang/bandit-bo

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Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

https://github.com/nsandholtz/hotspot_paper

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Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task

https://github.com/ntienvu/BOIL

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Bayesian Optimization for Iterative Learning

https://github.com/ntienvu/KnownOptimum_BO

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Knowing The What But Not The Where in Bayesian Optimization

https://github.com/olivomao/boassembler

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BOAssembler: a Bayesian Optimization Framework to Improve RNA-Seq Assembly Performance

https://github.com/onurboyar/Crystal-LSBO

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Crystal-LSBO: Automated Design of De Novo Crystals with Latent Space Bayesian Optimization

https://github.com/openml/continual-automl

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Adaptation Strategies for Automated Machine Learning on Evolving Data

https://github.com/optimal-pse-lab/humbo

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Human-Algorithm Collaborative Bayesian Optimization for Engineering Systems

https://github.com/oxfordcontrol/Bayesian-Optimization

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Distributionally Ambiguous Optimization Techniques for Batch Bayesian Optimization

https://github.com/paulsonlab/constrained_upper_quantile_bound

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No-Regret Constrained Bayesian Optimization of Noisy and Expensive Hybrid Models using Differentiable Quantile Function Approximations

https://github.com/pawelwm/h-louvain

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Modularity Based Community Detection in Hypergraphs

https://github.com/pescap/hpomax

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Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems

https://github.com/phantrdat/neuralbo

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Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks

https://github.com/pku-liang/HASCO

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HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation

https://github.com/pmsdapfmbf/duet

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DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks

https://github.com/pmy0124nus/wegp

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Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models

https://github.com/pratikrathore8/scalable_gp_inference

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Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project

https://github.com/predict-epfl/pdcbo

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Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

https://github.com/predict-epfl/pop-bo

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Principled Preferential Bayesian Optimization

https://github.com/predict-epfl/vacbo

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Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints

https://github.com/prishita123/curriculum_rl_for_driving

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Improving Environment Robustness of Deep Reinforcement Learning Approaches for Autonomous Racing Using Bayesian Optimization-based Curriculum Learning

https://github.com/probprog/bopp

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Bayesian Optimization for Probabilistic Programs

https://github.com/probprog/deodorant

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Bayesian Optimization for Probabilistic Programs

https://github.com/pulse-ml/momfbo-algorithm

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Leveraging Trust for Joint Multi-Objective and Multi-Fidelity Optimization

https://github.com/purushottamkar/esop

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Epidemiologically and Socio-economically Optimal Policies via Bayesian Optimization

https://github.com/pv-lab/ml-multiscale-droplets

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A Machine Learning and Computer Vision Approach to Rapidly Optimize Multiscale Droplet Generation

https://github.com/pv-lab/zombi

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Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI)

https://github.com/pythonpanda2/active-learning-md

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Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide

https://github.com/pytorch/botorch

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BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization

https://github.com/qianjanexie/pandorabayesopt

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Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index

https://github.com/qphong/bes-mp

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An Information-Theoretic Framework for Unifying Active Learning Problems

https://github.com/ranr01/miniBOP

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New Heuristics for Parallel and Scalable Bayesian Optimization

https://github.com/raulastudillo06/bofn

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Bayesian Optimization of Function Networks

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