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GPR

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

https://github.com/CliMA/CalibrateEmulateSample.jl

공식 코드

Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features

https://github.com/CliMA/EnsembleKalmanProcesses.jl

공식 코드

Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features

https://github.com/CliMA/RandomFeatures.jl

공식 코드

Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features

https://github.com/LiuHaiTao01/GPCnoise

공식 코드

Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods

https://github.com/Magica-Chen/gptp_multi_output

공식 코드

Multivariate Gaussian and Student$-t$ Process Regression for Multi-output Prediction

https://github.com/Pyxel0524/EDE-LGPR

공식 코드

EDENet: Echo Direction Encoding Network for Place Recognition Based on Ground Penetrating Radar

https://github.com/Qiqi-Dai/DMRF-UNet

공식 코드

DMRF-UNet: A Two-Stage Deep Learning Scheme for GPR Data Inversion under Heterogeneous Soil Conditions

https://github.com/TheochemUI/gpr_sella_repro

공식 코드

Efficient Implementation of Gaussian Process Regression Accelerated Saddle Point Searches with Application to Molecular Reactions

https://github.com/a-jd/npsn

공식 코드

Empirical Models for Multidimensional Regression of Fission Systems

https://github.com/adityasaini70/unravel

공식 코드

Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability

https://github.com/amornyosh/gpdp_ieee_ssp_2025

공식 코드

Overcoming Overfitting in Reinforcement Learning via Gaussian Process Diffusion Policy

https://github.com/aragagnin/hodemu

공식 코드

Satellite galaxy abundance dependency on cosmology in Magneticum simulations

https://github.com/baikeshe/gpr_epi_modeling

공식 코드

Modeling Epidemic Spread: A Gaussian Process Regression Approach

https://github.com/cvl-hub/gprn

공식 코드

SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation

https://github.com/damnull/lagcn

공식 코드

Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition

https://github.com/eilion/SA-GPR

공식 코드

Bayesian Inference Gaussian Process Multiproxy Alignment of Continuous Signals (BIGMACS): Applications for Paleoceanography

https://github.com/felixriese/hyperspectral-processing

공식 코드

Fusion of hyperspectral and ground penetrating radar to estimate soil moisture

https://github.com/galirage/gpr-bench

공식 코드

Ensuring Reproducibility in Generative AI Systems for General Use Cases: A Framework for Regression Testing and Open Datasets

https://github.com/grimmlab/evars-gpr

공식 코드

EVARS-GPR: EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Data

https://github.com/hfut-cv/lmt-gp

공식 코드

LMT-GP: Combined Latent Mean-Teacher and Gaussian Process for Semi-supervised Low-light Image Enhancement

https://github.com/himanshu258/constrained_gp_eos

공식 코드

Learning thermodynamically constrained equations of state with uncertainty

https://github.com/ivam-he/BernNet

공식 코드

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

https://github.com/ivam-he/chebnetii

공식 코드

Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited

https://github.com/jianhao2016/GPRGNN

공식 코드

Adaptive Universal Generalized PageRank Graph Neural Network

https://github.com/jingweio/dsf

공식 코드

Graph Neural Networks with Diverse Spectral Filtering

https://github.com/jules-leguy/bbomol

공식 코드

Surrogate-Based Black-Box Optimization Method for Costly Molecular Properties

https://github.com/jwangjie/An-Intuitive-Tutorial-to-Gaussian-Processes-Regression

공식 코드

An Intuitive Tutorial to Gaussian Process Regression

https://github.com/jwangjie/Gaussian-Processes-Regression-Tutorial

공식 코드

An Intuitive Tutorial to Gaussian Process Regression

https://github.com/jwangjie/gaussian-process-regression-tutorial

공식 코드

An Intuitive Tutorial to Gaussian Process Regression

https://github.com/kennethborup/gaussian_process_self_distillation

공식 코드

Self-Distillation for Gaussian Process Regression and Classification

https://github.com/kurtbutler/2024_attributions_paper

공식 코드

Explainable Learning with Gaussian Processes

https://github.com/kurtbutler/gp-knowledge

공식 코드

Trustworthy Prediction with Gaussian Process Knowledge Scores

https://github.com/littletigerhao/mt-gprmachine

공식 코드

Time Series Prediction by Multi-task GPR with Spatiotemporal Information Transformation

https://github.com/ljding94/gpr_pricing

공식 코드

Fast Derivative Valuation from Volatility Surfaces using Machine Learning

https://github.com/majsylw/gprMax/tree/feature/relaxation

공식 코드

Modelling Arbitrary Complex Dielectric Properties -- an automated implementation for gprMax

https://github.com/markusheinonen/adaptivegp

공식 코드

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo

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