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 926–950 of 2050 papers

TitleStatusHype
Multi-View Independent Component Analysis with Shared and Individual Sources—0
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors—0
Detection and Evaluation of Clusters within Sequential Data—0
MEDFAIR: Benchmarking Fairness for Medical ImagingCode0
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
Factor-Augmented Regularized Model for Hazard Regression—0
Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization—0
Feature-based model selection for object detection from point cloud data—0
A Bayesian constitutive model selection framework for biaxial mechanical testing of planar soft tissues: application to porcine aortic valves—0
Partial sequence labeling with structured Gaussian Processes—0
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs—0
Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time seriesCode0
Towards Deep Learning-aided Wireless Channel Estimation and Channel State Information Feedback for 6G—0
Model Selection in High-Dimensional Block-Sparse Linear Regression—0
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development—0
A Two-step Metropolis Hastings Method for Bayesian Empirical Likelihood Computation with Application to Bayesian Model Selection—0
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets—0
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution—0
Impact of Loss Model Selection on Power Semiconductor Lifetime Prediction in Electric Vehicles—0
Time Series Clustering with an EM algorithm for Mixtures of Linear Gaussian State Space ModelsCode0
Pushing the limits of fairness impossibility: Who's the fairest of them all?—0
Building Robust Machine Learning Models for Small Chemical Science Data: The Case of Shear Viscosity—0
SeNMFk-SPLIT: Large Corpora Topic Modeling by Semantic Non-negative Matrix Factorization with Automatic Model Selection—0
Meta Learning for High-dimensional Ising Model Selection Using _1-regularized Logistic Regression—0
Two-Stage Robust and Sparse Distributed Statistical Inference for Large-Scale Data—0
Show:102550
← PrevPage 38 of 82Next →

No leaderboard results yet.