GPR

Description from the archive archive 2025-07-28.

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 62 papers with code (270 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features
  30 Jun 2024 3 repositories listed
  Inspired by Bayesian ideas from GPR, this paper introduces a random objective function that is tailored for hyperparameter tuning of vector-valued random features.
• An Intuitive Tutorial to Gaussian Process Regression
  22 Sep 2020 3 repositories listed
  This tutorial is accessible to a broad audience, including those new to machine learning, ensuring a clear understanding of GPR fundamentals.
• GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
  12 Apr 2023 2 repositories listed
  In the realm of 3D-computer vision applications, point cloud few-shot learning plays a critical role.
• Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning
  31 May 2022 2 repositories listed
  To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test…
• Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
  25 Jun 2025 1 repository listed
  This study proposes a high-performance dual-parameter full waveform inversion framework (FWI) for ground-penetrating radar (GPR), accelerated through the hybrid compilation of CUDA kernel functions and PyTorch.
• Trustworthy Prediction with Gaussian Process Knowledge Scores
  23 Jun 2025 1 repository listed
  We demonstrate in several experiments that the knowledge score can anticipate when predictions from a GPR model are accurate, and that this anticipation improves performance in tasks such as anomaly detection,…
• Overcoming Overfitting in Reinforcement Learning via Gaussian Process Diffusion Policy
  16 Jun 2025 1 repository listed
  One of the key challenges that Reinforcement Learning (RL) faces is its limited capability to adapt to a change of data distribution caused by uncertainties.
• Fast Derivative Valuation from Volatility Surfaces using Machine Learning
  29 May 2025 1 repository listed
  From these synthetic market scenarios, we then compute high-accuracy valuations using conventional methodologies for two representative products: the fair strike of a variance swap and the price and Greeks of an…
• Efficient Implementation of Gaussian Process Regression Accelerated Saddle Point Searches with Application to Molecular Reactions
  18 May 2025 1 repository listed
  An order of magnitude reduction in the number of electronic structure calculations needed to reach the saddle point configurations is obtained by using the GPR compared to the dimer method.
• Ensuring Reproducibility in Generative AI Systems for General Use Cases: A Framework for Regression Testing and Open Datasets
  2 May 2025 1 repository listed
  Reproducibility and reliability remain pressing challenges for generative AI systems whose behavior can drift with each model update or prompt revision.
• Reservoir-enhanced Segment Anything Model for Subsurface Diagnosis
  26 Apr 2025 1 repository listed
  Urban roads and infrastructure, vital to city operations, face growing threats from subsurface anomalies like cracks and cavities.
• EDENet: Echo Direction Encoding Network for Place Recognition Based on Ground Penetrating Radar
  28 Feb 2025 1 repository listed
  Ground penetrating radar (GPR) based localization has gained significant recognition in robotics due to its ability to detect stable subsurface features, offering advantages in environments where traditional sensors…
• Interference Prediction Using Gaussian Process Regression and Management Framework for Critical Services in Local 6G Networks
  23 Jan 2025 1 repository listed
  The performance of the proposed approach is evaluated against two benchmarks prediction schemes, a moving average-based estimator and the ideal genie-aided estimator.
• SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation
  31 Dec 2024 1 repository listed
  In contrast, the large-scale visual model SAM, pre-trained on tens of millions of images from various domains and classes, possesses excellent generalizability.
• LMT-GP: Combined Latent Mean-Teacher and Gaussian Process for Semi-supervised Low-light Image Enhancement
  29 Aug 2024 1 repository listed
  Meanwhile, we use a mean-teacher-assisted Gaussian process learning strategy to establish a connection between the latent and pseudo-latent vectors obtained from the labeled and unlabeled data.
• Explainable Learning with Gaussian Processes
  11 Mar 2024 1 repository listed
  When using integrated gradients as an attribution method, we show that the attributions of a GPR model also follow a Gaussian process distribution, which quantifies the uncertainty in attribution arising from…
• Data-Driven Stochastic AC-OPF using Gaussian Processes
  17 Feb 2024 1 repository listed
  To solve the non-convex and computationally challenging CC AC-OPF problem, the proposed approach relies on a machine learning Gaussian process regression (GPR) model.
• Graph Neural Networks with Diverse Spectral Filtering
  14 Dec 2023 1 repository listed
  Spectral Graph Neural Networks (GNNs) have achieved tremendous success in graph machine learning, with polynomial filters applied for graph convolutions, where all nodes share the identical filter weights to mine their…
• Modeling Epidemic Spread: A Gaussian Process Regression Approach
  14 Dec 2023 1 repository listed
  We bound the variance of the predictions made by GPR, which quantifies the impact of epidemic data on the proposed model.
• Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR
  9 Aug 2023 1 repository listed
  To address these challenges, we introduce a novel methodology for the subgrade distress detection task by leveraging the multi-view information from 3D-GPR data.
• Learning thermodynamically constrained equations of state with uncertainty
  29 Jun 2023 1 repository listed
  Since there are inherent uncertainties in the calibration data (parametric uncertainty) and the assumed functional EOS form (model uncertainty), it is essential to perform uncertainty quantification (UQ) to improve…
• Language Knowledge-Assisted Representation Learning for Skeleton-Based Action Recognition
  21 May 2023 1 repository listed
  Also, humans have brain regions dedicated to understanding the minds of others and analyzing their intentions, such as the medial prefrontal cortex of the temporal lobe.
• 3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data Inversion
  9 May 2023 1 repository listed
  The reconstruction of the 3D permittivity map from ground-penetrating radar (GPR) data is of great importance for mapping subsurface environments and inspecting underground structural integrity.
• Self-Distillation for Gaussian Process Regression and Classification
  5 Apr 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We propose two approaches to extend the notion of knowledge distillation to Gaussian Process Regression (GPR) and Gaussian Process Classification (GPC); data-centric and distribution-centric.
• Robust and Scalable Gaussian Process Regression and Its Applications
  1 Jan 2023 1 repository listed
  This enables the application of Gaussian processes to a wide range of real data, which are often large-scale and contaminated by outliers.
• Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation
  1 Sep 2022 1 repository listed
  We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost.
• Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression
  17 Jul 2022 1 repository listed
  We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correlation energies of general electronic…
• Certified Graph Unlearning
  18 Jun 2022 1 repository listed
  For example, when unlearning 20% of the nodes on the Cora dataset, our approach suffers only a 0.
• DMRF-UNet: A Two-Stage Deep Learning Scheme for GPR Data Inversion under Heterogeneous Soil Conditions
  16 May 2022 1 repository listed
  In the first stage, a U-shape DNN with multi-receptive-field convolutions (MRF-UNet1) is built to remove the clutters due to inhomogeneity of the heterogeneous soil.
• JGPR: a computationally efficient multi-target Gaussian process regression algorithm
  11 May 2022 1 repository listed
  Multi-target regression algorithms are designed to predict multiple outputs at the same time, and allow us to take all output variables into account during the training phase.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.