专题:Gaussian Processes and Bayesian Inference

This cluster of papers focuses on the application of Gaussian Processes in machine learning, covering topics such as variational inference, sparse regression, Bayesian inference, deep learning, and probabilistic models. It also explores the use of Gaussian Processes for nonparametric methods, time series modelling, and handling big data.
最新文献
Estimating sparse regression models in multi-task learning and transfer learning through adaptive penalisation.

article Full Text OpenAlex

L2-norm posterior contraction in Gaussian models with unknown variance

article Full Text OpenAlex

Efficient training of Gaussian processes with tensor product structure

article Full Text OpenAlex

On Black-Box Optimization Problems Based on Bayesian System Modeling with Gaussian Processes

book-chapter Full Text OpenAlex

A Review on Applications of Gaussian Processes for Complex Control Systems

review Full Text OpenAlex

A greedy and optimistic clustering for leveraging individual covariate uncertainty

article Full Text OpenAlex

Study of the Possibility of Using 3D Printing in Low-Background Experiments

article Full Text OpenAlex

Assessing Methods for Estimating Microbial Lag Phase Duration: A Comparative Analysis Using S.cerevisiae Empirical and Simulated Data

article Full Text OpenAlex

Logistic models inspired by non-Gaussian statistics: an application to tumor growth

article Full Text OpenAlex

State Space Kriging Model for Emulating Nonlinear Stochastic Dynamical Systems with System Parameter Uncertainty

preprint Full Text OpenAlex

近5年高被引文献
Physics-informed machine learning

review Full Text OpenAlex 3810 FWCI46.024

Understanding deep learning (still) requires rethinking generalization

article Full Text OpenAlex 1685 FWCI160.623

Auto-Encoding Variational Bayes

article Full Text OpenAlex 988 FWCI144.258

Support Vector Regression

book-chapter Full Text OpenAlex 846 FWCI1.817

Hands-On Bayesian Neural Networks—A Tutorial for Deep Learning Users

article Full Text OpenAlex 558 FWCI64.78

PyMC: a modern, and comprehensive probabilistic programming framework in Python

article Full Text OpenAlex 519 FWCI72.115

Optimal ratio for data splitting

article Full Text OpenAlex 492 FWCI63.225

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

review Full Text OpenAlex 342 FWCI17.155

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

article Full Text OpenAlex 324 FWCI38.321

UltraNest - a robust, general purpose Bayesian inference engine

article Full Text OpenAlex 271 FWCI26.086