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regression

Papers

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Showing 601–625 of 9424 papers

TitleStatusHype
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking ClassifierCode1
Refined Risk Bounds for Unbounded Losses via Transductive Priors—0
Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds—0
A Distributed Lag Approach to the Generalised Dynamic Factor Model (GDFM)—0
High-Dimensional Gaussian Process Regression with Soft Kernel InterpolationCode0
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning ModelsCode2
Predicting Mortality and Functional Status Scores of Traumatic Brain Injury Patients using Supervised Machine Learning—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Understanding the Effect of GCN Convolutions in Regression Tasks—0
On the Gaussian process limit of Bayesian Additive Regression TreesCode0
Disentangling Genotype and Environment Specific Latent Features for Improved Trait Prediction using a Compositional Autoencoder—0
Noise-Aware Differentially Private Variational Inference—0
Conformal Prediction for Multimodal RegressionCode0
Target Strangeness: A Novel Conformal Prediction Difficulty EstimatorCode0
High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws—0
Adjusted Overfitting Regression—0
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor SearchCode2
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional TokensCode0
Generalized Resubstitution for Regression Error Estimation—0
Self-Supervised Learning for Time Series: A Review & Critique of FITSCode0
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression—0
regAL: Python Package for Active Learning of Regression Problems—0
A Kernel Perspective on Distillation-based Collaborative Learning—0
A Comparison of Baseline Models and a Transformer Network for SOC Prediction in Lithium-Ion Batteries—0
A Survey on Deep Learning-based Gaze Direction Regression: Searching for the State-of-the-art—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