Papers with Code 아카이브

Bayesian Optimization

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/ksehic/lassobench

공식 코드

LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso

https://github.com/lamda-bbo/mcts-transfer

공식 코드

Monte Carlo Tree Search based Space Transfer for Black-box Optimization

https://github.com/lamda-bbo/mcts-vs

공식 코드

Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization

https://github.com/lamda-bbo/sbokde

공식 코드

Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation

https://github.com/lamngo1/cma-meta-algorithm

공식 코드

High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy

https://github.com/lancopku/text-autoaugment

공식 코드

Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification

https://github.com/lasgroup/gosafeopt

공식 코드

Tuning Legged Locomotion Controllers via Safe Bayesian Optimization

https://github.com/lasgroup/lite

공식 코드

LITE: Efficiently Estimating Gaussian Probability of Maximality

https://github.com/leoiv/baxus

공식 코드

Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces

https://github.com/leoiv/bounce

공식 코드

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces

https://github.com/lfbo-ml/lfbo

공식 코드

A General Recipe for Likelihood-free Bayesian Optimization

https://github.com/lichang-chen/instructzero

공식 코드

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

https://github.com/lingxiaoyuan/chiral

공식 코드

Machine Learning-Guided Design of Non-Reciprocal and Asymmetric Elastic Chiral Metamaterials

https://github.com/liuj-2023/invtremo

공식 코드

Bayesian Inverse Transfer in Evolutionary Multiobjective Optimization

https://github.com/luinardi/hypermapper

공식 코드

HypBO: Accelerating Black-Box Scientific Experiments Using Experts' Hypotheses

https://github.com/ma921/adabatal

공식 코드

Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach

https://github.com/ma921/coexbo

공식 코드

Looping in the Human Collaborative and Explainable Bayesian Optimization

https://github.com/ma921/sober

공식 코드

SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces

https://github.com/machinelearninglifescience/corel

공식 코드

A Continuous Relaxation for Discrete Bayesian Optimization

https://github.com/maestro-project/confuciux

공식 코드

ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning

https://github.com/mahaitongdae/dbo

공식 코드

Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization

https://github.com/mahindrautela/bopinn

공식 코드

Bayesian optimized physics-informed neural network for estimating wave propagation velocities

https://github.com/mamadpierre/QCDS

공식 코드

Quantum Circuit Design Search

https://github.com/marialaurasantoni/ioh-profiler-hdbo-comparison

공식 코드

Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB

https://github.com/marketdesignresearch/BOCA

공식 코드

Bayesian Optimization-based Combinatorial Assignment

https://github.com/marketdesignresearch/NOMU

공식 코드

NOMU: Neural Optimization-based Model Uncertainty

https://github.com/markm541374/gpbo

공식 코드

Practical Bayesian Optimization for Variable Cost Objectives

https://github.com/martinjankowiak/saasbo

공식 코드

High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces

https://github.com/marwash25/non-sub-min

공식 코드

Optimal approximation for unconstrained non-submodular minimization

https://github.com/mathbon/discover-pinns-model

공식 코드

Discovering Physics-Informed Neural Networks Model for Solving Partial Differential Equations through Evolutionary Computation

https://github.com/mathieutuli/autohyper

공식 코드

Towards Robust and Automatic Hyper-Parameter Tunning

https://github.com/maxc01/addtree

공식 코드

Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation

https://github.com/mbinois/RRembo

공식 코드

On the choice of the low-dimensional domain for global optimization via random embeddings

https://github.com/mbzuai-nlp/audiojailbreak

공식 코드

Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models

https://github.com/meta-metrics/metametrics

공식 코드

MetaMetrics-MT: Tuning Meta-Metrics for Machine Translation via Human Preference Calibration

https://github.com/metabo-iclr2020/MetaBO

공식 코드

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization

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