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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/KUCognitiveInformaticsLab/PairwiseExpressionAnnotator

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HAPI: A Model for Learning Robot Facial Expressions from Human Preferences

https://github.com/KacperWyrwal/residual-deep-gps

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Residual Deep Gaussian Processes on Manifolds

https://github.com/Karim-53/Reinforcement-Learning-Malaria-Control-KDDCup-2019

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Policy Learning for Malaria Control

https://github.com/Kingsford-Group/vsbo

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Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection

https://github.com/KirillShmilovich/ActiveLearningCG

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Discovery of Self-Assembling $π$-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

https://github.com/LamNgo1/boids

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BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings

https://github.com/LeonResearch/GraphComBO

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Bayesian Optimization of Functions over Node Subsets in Graphs

https://github.com/LinLabNEU/Blackbox_ADMM

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On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

https://github.com/MLRG-CEFET-RJ/HBRKGA

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A Population-based Hybrid Approach to Hyperparameter Optimization for Neural Networks

https://github.com/MStarmans91/WORC

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An automated machine learning framework to optimize radiomics model construction validated on twelve clinical applications

https://github.com/MachineLearningLifeScience/hdbo_benchmark

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A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences

https://github.com/Markusmu93/J-CompChE-HPCBoTS

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Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems

https://github.com/MiriamKirchhoff/BO_for_EEG-TMS_phase

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Closed-Loop phase selection in EEG-TMS using Bayesian Optimization

https://github.com/Mitan/po-gp-ucb

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Private Outsourced Bayesian Optimization

https://github.com/NVlabs/condensa

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A Programmable Approach to Neural Network Compression

https://github.com/Networks-Learning/nevae

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NeVAE: A Deep Generative Model for Molecular Graphs

https://github.com/NoemieJaquier/GaBOtorch

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High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds

https://github.com/On-Point-RND/SeqNAS

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SeqNAS: Neural Architecture Search for Event Sequence Classification

https://github.com/OptCon/SafeBO_WKR

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Towards safe Bayesian optimization with Wiener kernel regression

https://github.com/PKU-DAIR/open-box

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Automated Hyperparameter Optimization Challenge at CIKM 2021 AnalyticCup

https://github.com/POSTECH-CVLab/Combinatorial-3D-Shape-Generation

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Combinatorial 3D Shape Generation via Sequential Assembly

https://github.com/PV-Lab/Benchmarking

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Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains

https://github.com/PV-Lab/SL-PerovskiteOpt

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Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing

https://github.com/PaulsonLab/CAGES

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CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization

https://github.com/PaulsonLab/MOBONS

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Multi-Objective Bayesian Optimization for Networked Black-Box Systems: A Path to Greener Profits and Smarter Designs

https://github.com/PedroFerreiradaCosta/FaceFitOpt

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Bayesian optimization for automatic design of face stimuli

https://github.com/PedroFerreiradaCosta/NeuroadaptiveEEG

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Neuroadaptive electroencephalography: a proof-of-principle study in infants

https://github.com/QUVA-Lab/COMBO

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Combinatorial Bayesian Optimization using the Graph Cartesian Product

https://github.com/Ryan-Rhys/Constrained-Bayesian-Optimisation-for-Automatic-Chemical-Design

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Constrained Bayesian Optimization for Automatic Chemical Design

https://github.com/Ryan-Rhys/Heteroscedastic-BO

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Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation

https://github.com/SMTorg/SMT

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High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft

https://github.com/StanfordAI4HI/HBBS

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A Hierarchical Approach to Scaling Batch Active Search Over Structured Data

https://github.com/TrustMLRG/GASP

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GASP: Efficient Black-Box Generation of Adversarial Suffixes for Jailbreaking LLMs

https://github.com/TsingQAQ/SANODEP

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System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization

https://github.com/UKPLab/tacl2020-interactive-ranking

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Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation

https://github.com/XiaoyanWork/DAMe

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DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism

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