SOTAVerified

Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1576–1600 of 2050 papers

TitleStatusHype
Bayesian Anomaly Detection and Classification—0
An information criterion for auxiliary variable selection in incomplete data analysis—0
Separating common (global and local) and distinct variation in multiple mixed types data setsCode0
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical SystemsCode0
Bayesian Image Classification with Deep Convolutional Gaussian Processes—0
Differential Description Length for Hyperparameter Selection in Machine Learning—0
Efficient Cross-Validation for Semi-Supervised Learning—0
Model Selection for Simulator-based Statistical Models: A Kernel Approach—0
Un modèle Bayésien de co-clustering de données mixtes—0
Learning Counterfactual Representations for Estimating Individual Dose-Response CurvesCode0
Fast Approximation and Estimation Bounds of Kernel Quadrature for Infinitely Wide Models—0
Learning for Multi-Model and Multi-Type Fitting—0
Comprehensive Evaluation of Deep Learning Architectures for Prediction of DNA/RNA Sequence Binding SpecificitiesCode0
Clustering Discrete-Valued Time Series—0
On the cross-validation bias due to unsupervised pre-processingCode0
Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship—0
lassopack: Model selection and prediction with regularized regression in Stata—0
An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation—0
Determining Principal Component Cardinality through the Principle of Minimum Description Length—0
Automated Adaptation Strategies for Stream LearningCode0
Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for TurbineGovernor and Excitation System—0
A Bayesian Model for Bivariate Causal Inference—0
Learning Representations from Dendrograms—0
Breaking the bonds of weak coupling: the dynamic causal modelling of oscillator amplitudes—0
Recurrent Neural Networks for Fuzz Testing Web BrowsersCode0
Show:102550
← PrevPage 64 of 82Next →

No leaderboard results yet.