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regression

Papers

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Showing 751–775 of 9424 papers

TitleStatusHype
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression—0
Extending Explainable Ensemble Trees (E2Tree) to regression contexts—0
Regression with Large Language Models for Materials and Molecular Property Prediction—0
Approximation Bounds for Recurrent Neural Networks with Application to Regression—0
Inference for Large Scale Regression Models with Dependent Errors—0
Lepskii Principle for Distributed Kernel Ridge Regression—0
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm—0
A semi-supervised learning using over-parameterized regression—0
Active learning for regression in engineering populations: A risk-informed approach—0
Enhancing Uncertainty Quantification in Drug Discovery with Censored Regression LabelsCode1
Reprojection Errors as Prompts for Efficient Scene Coordinate Regression—0
An Efficient and Generalizable Symbolic Regression Method for Time Series Analysis—0
A Unified Approach to Inferring Chemical Compounds with the Desired Aqueous SolubilityCode0
Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMsCode0
The Prevalence of Neural Collapse in Neural Multivariate Regression—0
Performance of Empirical Risk Minimization For Principal Component Regression—0
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality—0
RETAIN: Interactive Tool for Regression Testing Guided LLM Migration—0
Safety vs. Performance: How Multi-Objective Learning Reduces Barriers to Market Entry—0
Tensor network square root Kalman filter for online Gaussian process regression—0
Momentum Dynamics in Competitive Sports: A Multi-Model Analysis Using TOPSIS and Logistic Regression—0
Deep Learning for Multi-Country GDP Prediction: A Study of Model Performance and Data ImpactCode0
Demographic parity in regression and classification within the unawareness framework—0
Distribution Regression Difference-In-Differences—0
Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables—0
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All datasetsCalifornia Housing PricesConcrete Compressive StrengthMedical Cost Personal DatasetSynthetic: y = x * sin xADORECar_Price_Prediction

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