Papers with Code 아카이브

Bayesian Optimization

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/desy-ml/cheetah-demos

공식 코드

Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations

https://github.com/desy-ml/rl-vs-bo

공식 코드

Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning

https://github.com/dimplekochar/LEDRO

공식 코드

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits

https://github.com/dme65/pySOT

공식 코드

pySOT and POAP: An event-driven asynchronous framework for surrogate optimization

https://github.com/dragonfly/dragonfly

공식 코드

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

https://github.com/dstl/yawning-titan

공식 코드

Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation

https://github.com/dsweet99/yubo

공식 코드

Optimal Initialization of Batch Bayesian Optimization

https://github.com/elamrireda/EFISUR

공식 코드

A sampling criterion for constrained Bayesian optimization with uncertainties

https://github.com/elfi-dev/elfi

공식 코드

ELFI: Engine for Likelihood-Free Inference

https://github.com/elifcerengokyildirim/adacl

공식 코드

AdaCL:Adaptive Continual Learning

https://github.com/emicore/emicore

공식 코드

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

https://github.com/ennosigaeon/auto-sktime

공식 코드

auto-sktime: Automated Time Series Forecasting

https://github.com/enricocrovini/BBO-via-PGF

공식 코드

Batch Bayesian Optimization via Particle Gradient Flows

https://github.com/erfmah/answering_graph_queries

공식 코드

Deep Generative Models for Subgraph Prediction

https://github.com/eric-vader/HD-BO-Additive-Models

공식 코드

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models

https://github.com/ericlee0803/GP_Derivatives

공식 코드

Scaling Gaussian Process Regression with Derivatives

https://github.com/ericlee0803/lookahead_release

공식 코드

Efficient Rollout Strategies for Bayesian Optimization

https://github.com/esiivola/hdssbo

공식 코드

Good practices for Bayesian Optimization of high dimensional structured spaces

https://github.com/esiivola/vdsobo

공식 코드

Correcting boundary over-exploration deficiencies in Bayesian optimization with virtual derivative sign observations

https://github.com/esl-sun/labcat

공식 코드

LABCAT: Locally adaptive Bayesian optimization using principal-component-aligned trust regions

https://github.com/evensgn/hyperbo

공식 코드

HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes

https://github.com/ewendawi/llamea-bo

공식 코드

LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms

https://github.com/experimental-design/bofire

공식 코드

BoFire: Bayesian Optimization Framework Intended for Real Experiments

https://github.com/facebookresearch/ContextualBO

공식 코드

Bayesian Optimization with High-Dimensional Outputs

https://github.com/facebookresearch/LaMCTS

공식 코드

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

https://github.com/facebookresearch/alebo

공식 코드

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization

https://github.com/facebookresearch/bo_pr

공식 코드

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

https://github.com/facebookresearch/heterogeneous_botl

공식 코드

Sample-Efficient Bayesian Optimization with Transfer Learning for Heterogeneous Search Spaces

https://github.com/facebookresearch/preference-exploration

공식 코드

Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes

https://github.com/facebookresearch/qeubo

공식 코드

qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization

https://github.com/facebookresearch/robust_mobo

공식 코드

Robust Multi-Objective Bayesian Optimization Under Input Noise

https://github.com/facebookresearch/sparsebo

공식 코드

Sparse Bayesian Optimization

https://github.com/facebookresearch/sustainableconcrete

공식 코드

Sustainable Concrete via Bayesian Optimization

https://github.com/fanhanwei/bocr

공식 코드

Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning

https://github.com/fanhanwei/fnn_mfrl_archdse

공식 코드

Explainable Fuzzy Neural Network with Multi-Fidelity Reinforcement Learning for Micro-Architecture Design Space Exploration

https://github.com/faosorios/heavy

공식 코드

Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization

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