NGBoost: Natural Gradient Boosting for Probabilistic Prediction

8 October 2019

Papers citing "NGBoost: Natural Gradient Boosting for Probabilistic Prediction"

31 / 31 papers shown

Title
LabTOP: A Unified Model for Lab Test Outcome Prediction on Electronic Health Records Sujeong Im Jungwoo Oh Edward Choi BDL LM&MA 53 0 0 20 Feb 2025
Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning Jiang Chang Deekshith Basvoju Aleksandar Vakanski Indrajit Charit Min Xian AI4CE 39 0 0 28 Jan 2025
Analyzing Spatio-Temporal Dynamics of Dissolved Oxygen for the River Thames using Superstatistical Methods and Machine Learning Hankun He Takuya Boehringer Benjamin Schäfer Kate Heppell Christian Beck 62 3 0 10 Jan 2025
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks Fuhang Liang Rucong Xu Deng Lin OOD 45 0 0 10 Jan 2025
Deep Learning for Ophthalmology: The State-of-the-Art and Future Trends Duy M. Nguyen Hasan Md Tusfiqur Alam Trung Quoc Nguyen Devansh Srivastav H. Profitlich Ngan Le Daniel Sonntag 49 2 0 07 Jan 2025
NRGBoost: Energy-Based Generative Boosted Trees João Bravo 48 0 0 04 Oct 2024
Forecasting with Hyper-Trees Alexander März Kashif Rasul 46 0 0 13 May 2024
Offensive Lineup Analysis in Basketball with Clustering Players Based on Shooting Style and Offensive Role Kazuhiro Yamada Keisuke Fujii 19 0 0 04 Mar 2024
Simulation Based Bayesian Optimization Roi Naveiro Becky Tang 32 0 0 19 Jan 2024
Ensemble-based Hybrid Optimization of Bayesian Neural Networks and Traditional Machine Learning Algorithms Peiwen Tan BDL 29 1 0 09 Oct 2023
ASDL: A Unified Interface for Gradient Preconditioning in PyTorch Kazuki Osawa Satoki Ishikawa Rio Yokota Shigang Li Torsten Hoefler ODL 51 14 0 08 May 2023
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean Anton Thielmann René-Marcel Kruse Thomas Kneib Benjamin Säfken 32 12 0 27 Jan 2023
Scalable Estimation for Structured Additive Distributional Regression Nikolaus Umlauf Johannes Seiler Mattias Wetscher T. Simon S. Lang Nadja Klein 21 6 0 13 Jan 2023
Nonparametric Probabilistic Regression with Coarse Learners B. Lucena 30 0 0 28 Oct 2022
Uncertainty in Extreme Multi-label Classification Jyun-Yu Jiang Wei-Cheng Chang Jiong Zhong Cho-Jui Hsieh Hsiang-Fu Yu UQCV 16 0 0 18 Oct 2022
TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method Jiaqi Luo Zihao Wei Junkai Man Shi-qian Xu 29 8 0 28 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 37 4 0 17 Sep 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 32 28 0 17 Jun 2022
Classification of datasets with imputed missing values: does imputation quality matter? Tolou Shadbahr M. Roberts Jan Stanczuk J. Gilbey P. Teare ... T. Mirtti A. Rannikko J. Aston Jing Tang Carola-Bibiane Schönlieb 37 52 0 16 Jun 2022
Probabilistic Models for Manufacturing Lead Times Recep Yusuf Bekci Yacine Mahdid Jinling Xing Nikita Letov Ying Zhang Zahid Pasha 27 0 0 28 Apr 2022
Look back, look around: a systematic analysis of effective predictors for new outlinks in focused Web crawling Thi Kim Nhung Dang Doina Bucur Berk Atil Guillaume Pitel Frank Ruis H. Kadkhodaei Exensa 24 6 0 09 Nov 2021
Generalized XGBoost Method Yang Guang 14 4 0 15 Sep 2021
An Interpretable Probabilistic Model for Short-Term Solar Power Forecasting Using Natural Gradient Boosting Georgios Mitrentsis H. Lens 14 106 0 05 Aug 2021
GBHT: Gradient Boosting Histogram Transform for Density Estimation Jingyi Cui H. Hang Yisen Wang Zhouchen Lin 30 9 0 10 Jun 2021
Multivariate Probabilistic Regression with Natural Gradient Boosting Michael O’Malley A. Sykulski R. Lumpkin Alejandro Schuler BDL 30 7 0 07 Jun 2021
How Powerful are Performance Predictors in Neural Architecture Search? Colin White Arber Zela Binxin Ru Yang Liu Frank Hutter 22 126 0 02 Apr 2021
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models E. Zelikman Sharon Zhou Jeremy Irvin Cooper D. Raterink Hao Sheng Anand Avati Jack Kelly Ram Rajagopal A. Ng D. Gagne 23 12 0 09 Oct 2020
Kaggle forecasting competitions: An overlooked learning opportunity Casper Solheim Bojer Jens Peder Meldgaard AI4TS 21 206 0 16 Sep 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 28 94 0 18 Jun 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015