Noisy Inputs, Sharper Predictions: Gaussian Process Regression Put to the Test
A systematic synthetic study shows first-order Noisy Input Gaussian Process Regression sharply outperforms standard GP at high input noise, while ...
A systematic synthetic study shows first-order Noisy Input Gaussian Process Regression sharply outperforms standard GP at high input noise, while ...
A meta-analysis of 103 Chinese school surveys reports a pooled screening-positive rate of 3.43% and a radiographically confirmed scoliosis prevalence ...
Scientists attached statistically guaranteed prediction intervals to an epigenetic age clock, achieving near-nominal coverage with only 16 CpG sites.
A comparative study of seven uncertainty-aware machine learning frameworks on real-world cargo EV data shows trade-offs between prediction accuracy, interval ...
A condition-stratified study of westbound Interstate I-94 found that XGBoost without weather variables delivered the most accurate hour-ahead traffic forecasts.
A study in Guangxi, China, combined UAV-LiDAR with NGBoost to predict forest stock volume as full probability distributions, achieving an ...
Researchers have introduced Conformalized Selective Regression, a framework that uses conformal prediction to let regression models abstain when uncertainty is ...
A study of 40 months of aggregated Indian rainfall data found that a parsimonious seasonal ARIMA model matched a seasonal-naive ...
A new study finds XGBoost reduces airline route passenger-traffic forecast error by 16.72 percent versus a naive benchmark, while showing ...
An umbrella review of fourteen meta-analyses finds patellar resurfacing in primary total knee replacement reduces reoperation risk but does not ...
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© 2025 Scienmag - Science Magazine