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regression

Papers

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Showing 4101–4150 of 9424 papers

TitleStatusHype
Deep Belief Networks Based Feature Generation and Regression for Predicting Wind Power—0
Deep Bayesian Estimation for Dynamic Treatment Regimes with a Long Follow-up Time—0
Attentional Graph Neural Network Is All You Need for Robust Massive Network Localization—0
Identifying Nominals with No Head Match Co-references Using Deep Learning—0
Alleviating Overfitting in Transformation-Interaction-Rational Symbolic Regression with Multi-Objective Optimization—0
Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization—0
AcED: Accurate and Edge-consistent Monocular Depth Estimation—0
A t-SNE Based Classification Approach to Compositional Microbiome Data—0
Debiased Machine Learning of Aggregated Intersection Bounds and Other Causal Parameters—0
Identification of Regression Models with a Misclassified and Endogenous Binary Regressor—0
Decreasing Weighted Sorted _1 Regularization—0
Decoupling the Curve Modeling and Pavement Regression for Lane Detection—0
A Tree Architecture of LSTM Networks for Sequential Regression with Missing Data—0
Decoupling Shrinkage and Selection for the Bayesian Quantile Regression—0
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier—0
A Linear Approach to Data Poisoning—0
Building Energy Efficiency through Advanced Regression Models and Metaheuristic Techniques for Sustainable Management—0
Identifying Nonlinear 1-Step Causal Influences in Presence of Latent Variables—0
Decoupling Features and Coordinates for Few-shot RGB Relocalization—0
Decoupled Sparse Gaussian Processes Components]Decoupled Sparse Gaussian Processes Components : Separating Decision Making from Data Manifold Fitting—0
A Likelihood Ratio Framework for High Dimensional Semiparametric Regression—0
Decoupled IoU Regression for Object Detection—0
Decoupled and Interactive Regression Modeling for High-performance One-stage 3D Object Detection—0
Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression—0
DECOrrelated feature space partitioning for distributed sparse regression—0
A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation—0
Atmospheric Influence on the Path Loss at High Frequencies for Deployment of 5G Cellular Communication Networks—0
Adaptive distributed methods under communication constraints—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
A deep learning approach for analyzing the composition of chemometric data—0
Deconvoluting Kernel Density Estimation and Regression for Locally Differentially Private Data—0
Decomposition of Differences in Distribution under Sample Selection and the Gender Wage Gap—0
A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Models—0
Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes—0
Decomposing Isotonic Regression for Efficiently Solving Large Problems—0
A Three-Feature Model to Predict Colour Change Blindness—0
A Lightweight Regression Method to Infer Psycholinguistic Properties for Brazilian Portuguese—0
Decomposable Sparse Tensor on Tensor Regression—0
A Theory of Hyperbolic Prototype Learning—0
Decoding of finger trajectory from ECoG using deep learning—0
Decoding Mean Field Games from Population and Environment Observations By Gaussian Processes—0
A Theoretical Study of The Effects of Adversarial Attacks on Sparse Regression—0
A Lightweight Domain Adaptive Absolute Pose Regressor Using Barlow Twins Objective—0
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos—0
Identification of Intraday False Data Injection Attack on DER Dispatch Signals—0
Identifying Real Estate Opportunities using Machine Learning—0
A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression—0
Decision Concept Lattice vs. Decision Trees and Random Forests—0
(Decision and regression) tree ensemble based kernels for regression and classification—0
A Theoretical Analysis of Logistic Regression and Bayesian Classifiers—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