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regression

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Showing 4701–4750 of 9424 papers

TitleStatusHype
Equivalence of Convergence Rates of Posterior Distributions and Bayes Estimators for Functions and Nonparametric Functionals—0
Equivalence of Kernel Machine Regression and Kernel Distance Covariance for Multidimensional Trait Association Studies—0
Equivalence of Learning Algorithms—0
Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees—0
ERM and RERM are optimal estimators for regression problems when malicious outliers corrupt the labels—0
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers—0
Error Analysis of Generalized Nyström Kernel Regression—0
Error analysis of regularized least-square regression with Fredholm kernel—0
Error Asymmetry in Causal and Anticausal Regression—0
Error Bounds for Piecewise Smooth and Switching Regression—0
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions—0
Error Bounds of the Invariant Statistics in Machine Learning of Ergodic Itô Diffusions—0
Error Correcting Algorithms for Sparsely Correlated Regressors—0
Error Correcting Algorithms for Sparsely Correlated Regressors—0
Error Distribution Smoothing:Advancing Low-Dimensional Imbalanced Regression—0
Error-in-variables modelling for operator learning—0
Error Parity Fairness: Testing for Group Fairness in Regression Tasks—0
Error Reduction from Stacked Regressions—0
Aleatoric uncertainty for Errors-in-Variables models in deep regression—0
Errors-in-variables Fréchet Regression with Low-rank Covariate Approximation—0
Efficient Epistemic Uncertainty Estimation in Regression Ensemble Models Using Pairwise-Distance Estimators—0
espiownage: Tracking Transients in Steelpan Drum Strikes Using Surveillance Technology—0
Estimates on Learning Rates for Multi-Penalty Distribution Regression—0
Estimating biomass migration parameters by analyzing the spatial behavior of the fishing fleet—0
Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques—0
Estimating Chlorophyll a Concentrations of Several Inland Waters with Hyperspectral Data and Machine Learning Models—0
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning—0
Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models—0
Estimating fire Duration using regression methods—0
Estimating friction coefficient using generative modelling—0
Estimating Individual Responses when Tomorrow Matters—0
Estimating location parameters in entangled single-sample distributions—0
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding—0
Estimating motion with principal component regression strategies—0
Estimating nonlinear regression errors without doing regression—0
Estimating Numbers without Regression—0
Estimating oil and gas recovery factors via machine learning: Database-dependent accuracy and reliability—0
Estimating regression errors without ground truth values—0
Estimating Regression Predictive Distributions with Sample Networks—0
Estimating Spillover Effects in the Presence of Isolated Nodes—0
Estimating Task Completion Times for Network Rollouts using Statistical Models within Partitioning-based Regression Methods—0
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression—0
Estimating the minimizer and the minimum value of a regression function under passive design—0
Estimating the time-lapse between medical insurance reimbursement with non-parametric regression models—0
Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression—0
Estimating Unbounded Density Ratios: Applications in Error Control under Covariate Shift—0
Estimating vector fields using sparse basis field expansions—0
Estimation Algorithm Non-Stationary Frequency of the Sinusoidal Signal—0
Estimation and Applications of Quantile Regression for Binary Longitudinal Data—0
Estimation and Inference by Stochastic Optimization: Three Examples—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.79—Unverified
2Baseline RegressionR2 Score0.58—Unverified
3Mimic / SurrogateR2 Score0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.86—Unverified
2Baseline RegressionR2 Score0.59—Unverified
3Mimic / SurrogateR2 Score0.58—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.87—Unverified
2Baseline RegressionR2 Score0.78—Unverified
3Mimic / SurrogateR2 Score0.78—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.98—Unverified
2Baseline RegressionR2 Score-0.01—Unverified
3Mimic / SurrogateR2 Score-0.01—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoost-MACCSmicro-averaged RMSE0.93—Unverified
2RF-ToxPrintchemical macro-average RMSE0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1Linear and Decision Tree RegressionR Squared86.84—Unverified