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 801–850 of 2050 papers

TitleStatusHype
UniASM: Binary Code Similarity Detection without Fine-tuningCode1
Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian QuadratureCode1
Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach—0
TRScore: A Novel GPT-based Readability Scorer for ASR Segmentation and Punctuation model evaluation and selection—0
Which is the best model for my data?—0
Improving Group Lasso for high-dimensional categorical data—0
Post-Selection Confidence Bounds for Prediction PerformanceCode0
360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter TuningCode1
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular dataCode1
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal TransportCode0
XAI for transparent wind turbine power curve modelsCode1
Scalable Bayesian Transformed Gaussian Processes—0
Graph Anomaly Detection with Unsupervised GNNsCode1
Measures of Information Reflect Memorization Patterns—0
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data—0
LEATHER: A Framework for Learning to Generate Human-like Text in DialogueCode0
On the calibration of underrepresented classes in LiDAR-based semantic segmentation—0
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble LearningCode0
PARAGEN : A Parallel Generation ToolkitCode1
To tree or not to tree? Assessing the impact of smoothing the decision boundaries—0
Multi-View Independent Component Analysis with Shared and Individual Sources—0
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
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
Unsupervised Model Selection for Time-series Anomaly DetectionCode1
A Bayesian constitutive model selection framework for biaxial mechanical testing of planar soft tissues: application to porcine aortic valves—0
Feature-based model selection for object detection from point cloud data—0
Entropic Descent Archetypal Analysis for Blind Hyperspectral UnmixingCode1
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
IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning PerspectiveCode2
Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time seriesCode0
A new family of Constitutive Artificial Neural Networks towards automated model discoveryCode1
clusterBMA: Bayesian model averaging for clusteringCode1
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
A Two-step Metropolis Hastings Method for Bayesian Empirical Likelihood Computation with Application to Bayesian Model Selection—0
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development—0
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution—0
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets—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
Show:102550
← PrevPage 17 of 41Next →

No leaderboard results yet.