SOTAVerified

Gaussian Processes

Gaussian Processes is a powerful framework for several machine learning tasks such as regression, classification and inference. Given a finite set of input output training data that is generated out of a fixed (but possibly unknown) function, the framework models the unknown function as a stochastic process such that the training outputs are a finite number of jointly Gaussian random variables, whose properties can then be used to infer the statistics (the mean and variance) of the function at test values of input.

Source: Sequential Randomized Matrix Factorization for Gaussian Processes: Efficient Predictions and Hyper-parameter Optimization

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1651–1700 of 1963 papers

TitleStatusHype
Subset-of-Data Variational Inference for Deep Gaussian-Processes RegressionCode0
Modulating Scalable Gaussian Processes for Expressive Statistical LearningCode0
Data-Driven Stochastic AC-OPF using Gaussian ProcessesCode0
Mondrian Forests for Large-Scale Regression when Uncertainty MattersCode0
Monotonic Gaussian Process FlowCode0
Quantum-Assisted Hilbert-Space Gaussian Process RegressionCode0
Similarity measure for sparse time course data based on Gaussian processesCode0
Simulation Based Bayesian OptimizationCode0
Simultaneous and Meshfree Topology Optimization with Physics-informed Gaussian ProcessesCode0
Random Feature Expansions for Deep Gaussian ProcessesCode0
Morphable Face Models - An Open FrameworkCode0
Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimizationCode0
Efficient Deep Gaussian Process Models for Variable-Sized InputCode0
Benchmarking optimality of time series classification methods in distinguishing diffusionsCode0
Randomly Projected Additive Gaussian Processes for RegressionCode0
Gaussian Process Priors for Boundary Value Problems of Linear Partial Differential EquationsCode0
A Learnable Safety MeasureCode0
Gaussian Process Random FieldsCode0
Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian ProcessesCode0
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian ProcessesCode0
Adaptive Basis Function Selection for Computationally Efficient PredictionsCode0
Gaussian Process Regression NetworksCode0
Dynamic Online Ensembles of Basis ExpansionsCode0
Data-driven Approach for Interpolation of Sparse DataCode0
Multi-fidelity Hierarchical Neural ProcessesCode0
Multi-Fidelity High-Order Gaussian Processes for Physical SimulationCode0
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical ApplicationsCode0
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive OrdersCode0
Data-driven Aerodynamic Analysis of Structures using Gaussian ProcessesCode0
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact SupervisionCode0
Multi-level CNN for lung nodule classification with Gaussian Process assisted hyperparameter optimizationCode0
Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial LibrariesCode0
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite NetworksCode0
Raven's Progressive Matrices Completion with Latent Gaussian Process PriorsCode0
Generalized Variational Inference: Three arguments for deriving new PosteriorsCode0
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep LearningCode0
Automatic Construction and Natural-Language Description of Nonparametric Regression ModelsCode0
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with DerivativesCode0
Multi-output Gaussian Processes for Uncertainty-aware Recommender SystemsCode0
Multi-Output Gaussian Processes for Graph-Structured DataCode0
Variational zero-inflated Gaussian processes with sparse kernelsCode0
Multioutput Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard AssessmentCode0
Global Convolutional Neural ProcessesCode0
Dynamic Bayesian Learning for Spatiotemporal Mechanistic ModelsCode0
Bayesian Structured Prediction Using Gaussian ProcessesCode0
A Gaussian Process-based Streaming Algorithm for Prediction of Time Series With Regimes and OutliersCode0
Multi-resolution Multi-task Gaussian ProcessesCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
Global universal approximation of functional input maps on weighted spacesCode0
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process ModelsCode0
Show:102550
← PrevPage 34 of 40Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ICKy, periodicRoot mean square error (RMSE)0.03—Unverified