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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/baptistar/BOCS

공식 코드

Bayesian Optimization of Combinatorial Structures

https://github.com/befelix/SafeOpt

공식 코드

Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics

https://github.com/belakaria/MESMO

공식 코드

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization

https://github.com/belakaria/MESMOC

공식 코드

Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints

https://github.com/belakaria/USEMOC

공식 코드

Uncertainty aware Search Framework for Multi-Objective Bayesian Optimization with Constraints

https://github.com/belakaria/imoca

공식 코드

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization

https://github.com/belakaria/mf-osemo

공식 코드

Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization

https://github.com/belakaria/usemo

공식 코드

Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization

https://github.com/ben-hawks/pytorch-jet-classify

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Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference

https://github.com/benmltu/jes

공식 코드

Joint Entropy Search for Multi-objective Bayesian Optimization

https://github.com/benmltu/scalarize

공식 코드

Multi-objective optimisation via the R2 utilities

https://github.com/beomjoonkim/MetaLearnBO

공식 코드

Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior

https://github.com/bghojogh/Fitting-Mixture-Distribution

공식 코드

Fitting A Mixture Distribution to Data: Tutorial

https://github.com/bhouri0412/rpn_bo

공식 코드

Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks

https://github.com/billzxl/dil-gp

공식 코드

Domain Invariant Learning for Gaussian Processes and Bayesian Exploration

https://github.com/bionicvisionlab/2023-neurips-hilo

공식 코드

Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses

https://github.com/blindedjoy/RcTorch

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Unsupervised Reservoir Computing for Solving Ordinary Differential Equations

https://github.com/boettiger-lab/rl4fisheries

공식 코드

Using machine learning to inform harvest control rule design in complex fishery settings

https://github.com/boschresearch/MetaBO

공식 코드

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization

https://github.com/boschresearch/NoisyInputEntropySearch

공식 코드

Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization

https://github.com/boschresearch/amor-struct-gp

공식 코드

Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels

https://github.com/boschresearch/bosot

공식 코드

Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport

https://github.com/boschresearch/meta-learning-likelihood-free-bayesian-optimization

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MALIBO: Meta-learning for Likelihood-free Bayesian Optimization

https://github.com/boschresearch/transfergpbo

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Transfer Learning with Gaussian Processes for Bayesian Optimization

https://github.com/boschresearch/transfersafesequentiallearning

공식 코드

Global Safe Sequential Learning via Efficient Knowledge Transfer

https://github.com/bostanabad-research-group/gp-plus

공식 코드

GP+: A Python Library for Kernel-based learning via Gaussian Processes

https://github.com/brunzema/uitvbo

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On Controller Tuning with Time-Varying Bayesian Optimization

https://github.com/callowbird/Harmonica

공식 코드

Hyperparameter Optimization: A Spectral Approach

https://github.com/cambridge-mlg/expressiveness-approx-bnns

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On the Expressiveness of Approximate Inference in Bayesian Neural Networks

https://github.com/cambridge-mlg/sgd-gp

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Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent

https://github.com/cambridgeltl/autopeft

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AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning

https://github.com/cardio-ai/mfvi-dip-mia

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Posterior temperature optimized Bayesian models for inverse problems in medical imaging

https://github.com/cc-hpc-itwm/HPO_LazyGPR

공식 코드

Scalable Hyperparameter Optimization with Lazy Gaussian Processes

https://github.com/cc-hpc-itwm/PHS

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PHS: A Toolbox for Parallel Hyperparameter Search

https://github.com/cenyou/transfersafesequentiallearning

공식 코드

Global Safe Sequential Learning via Efficient Knowledge Transfer

https://github.com/chaeyoon-jang/bomf

공식 코드

Model Fusion through Bayesian Optimization in Language Model Fine-Tuning

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