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quantile regression

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TitleStatusHype
Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks—0
fastkqr: A Fast Algorithm for Kernel Quantile Regression—0
Federated Smoothing Proximal Gradient for Quantile Regression with Non-Convex Penalties—0
Probabilistic energy forecasting through quantile regression in reproducing kernel Hilbert spacesCode0
Quantile Regression using Random Forest Proximities—0
Decentralized Smoothing ADMM for Quantile Regression with Non-Convex Sparse Penalties—0
Flusion: Integrating multiple data sources for accurate influenza predictions—0
Ensemble quantile-based deep learning framework for streamflow and flood prediction in Australian catchments—0
Conformal Thresholded Intervals for Efficient RegressionCode0
Conditional Quantile Estimation for Uncertain Watch Time in Short-Video RecommendationCode0
Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble ForecastsCode0
Probabilistic Conformal Prediction with Approximate Conditional Validity—0
Combinations of distributional regression algorithms with application in uncertainty estimation of corrected satellite precipitation products—0
Enhancing reliability in prediction intervals using point forecasters: Heteroscedastic Quantile Regression and Width-Adaptive Conformal InferenceCode0
Towards Deep Learning for Predicting Microbial Fuel Cell Energy Output—0
Stacking for Probabilistic Short-term Load Forecasting—0
Relaxed Quantile Regression: Prediction Intervals for Asymmetric NoiseCode0
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing—0
AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained OptimizationCode0
SEMF: Supervised Expectation-Maximization Framework for Predicting IntervalsCode0
Data-Driven Personalized Energy Consumption Range Estimation for Plug-in Hybrid Electric Vehicles in Urban Traffic—0
Kernel-based Optimally Weighted Conformal Prediction Intervals—0
ReModels: Quantile Regression Averaging models—0
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support RecoveryCode0
A quantile-based nonadditive fixed effects model—0
Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression—0
Heart Rate and Body Temperature Relationship in Children Admitted to PICU -- A Machine Learning Approach—0
Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression—0
Fused LASSO as Non-Crossing Quantile Regression—0
Ensemble learning for predictive uncertainty estimation with application to the correction of satellite precipitation products—0
Heterogeneous Image-based Classification Using Distributional Data Analysis—0
Fast Algorithms for Quantile Regression with Selection—0
Conservative and Risk-Aware Offline Multi-Agent Reinforcement LearningCode0
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement LearningCode0
Multiple Yield Curve Modeling and Forecasting using Deep Learning—0
Does green innovation crowd out other innovation of firms? Based on the extended CDM model and unconditional quantile regressions—0
Local Identification in Instrumental Variable Multivariate Quantile Regression Models—0
Simulation-Based Inference with Quantile RegressionCode0
Beyond mirkwood: Enhancing SED Modeling with Conformal Predictions—0
Membership Inference Attacks on Diffusion Models via Quantile Regression—0
Deep Ensembles Meets Quantile Regression: Uncertainty-aware Imputation for Time Series—0
Learning to Simulate: Generative Metamodeling via Quantile Regression—0
A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market—0
Uncertainty estimation of machine learning spatial precipitation predictions from satellite data—0
Bayesian Quantile Regression with Subset Selection: A Decision Analysis Perspective—0
Use of Deep Neural Networks for Uncertain Stress Functions with Extensions to Impact Mechanics—0
Exploring a new machine learning based probabilistic model for high-resolution indoor radon mapping, using the German indoor radon survey data—0
Smoothed instrumental variables quantile regression—0
Towards a Unified Analysis of Kernel-based Methods Under Covariate ShiftCode0
Probabilistic Load Forecasting of Distribution Power Systems based on Empirical Copulas—0
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