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NGBoost: Natural Gradient Boosting for Probabilistic Prediction

8 October 2019

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

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Title
LabTOP: A Unified Model for Lab Test Outcome Prediction on Electronic Health Records Sujeong Im Jungwoo Oh Edward Choi BDL LM&MA 108 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 113 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 214 4 0 10 Jan 2025
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks Fuhang Liang Rucong Xu Deng Lin OOD 77 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 90 3 0 07 Jan 2025
Supervised Score-Based Modeling by Gradient Boosting Changyuan Zhao Hongyang Du Guangyuan Liu Dusit Niyato DiffM 86 0 0 02 Nov 2024
NRGBoost: Energy-Based Generative Boosted Trees João Bravo 130 0 0 04 Oct 2024
Conformal Prediction for Dose-Response Models with Continuous Treatments Jarne Verhaeghe Jef Jonkers Sofie Van Hoecke 58 0 0 30 Sep 2024
Boosted generalized normal distributions: Integrating machine learning with operations knowledge Ragip Gurlek F. Véricourt Donald K. K. Lee AI4CE 46 1 0 26 Jul 2024
Transformers with Stochastic Competition for Tabular Data Modelling Andreas Voskou Charalambos Christoforou S. Chatzis LMTD 92 1 0 18 Jul 2024
Gradient Boosting Reinforcement Learning Benjamin Fuhrer Chen Tessler Gal Dalal OffRL AI4CE 181 3 0 11 Jul 2024
Unmasking Trees for Tabular Data Calvin McCarter 90 3 0 08 Jul 2024
Treeffuser: Probabilistic Predictions via Conditional Diffusions with Gradient-Boosted Trees Nicolas Beltran-Velez Alessandro Antonio Grande Achille Nazaret A. Kucukelbir David M. Blei 88 3 0 11 Jun 2024
Generative modeling of density regression through tree flows Zhuoqun Wang Naoki Awaya Li Ma DRL 59 0 0 07 Jun 2024
Diffusion Boosted Trees Xizewen Han Mingyuan Zhou AI4CE 102 0 0 03 Jun 2024
Wasserstein Gradient Boosting: A General Framework with Applications to Posterior Regression Takuo Matsubara 46 0 0 15 May 2024
Forecasting with Hyper-Trees Alexander März Kashif Rasul 127 0 0 13 May 2024
Surprisingly Strong Performance Prediction with Neural Graph Features Gabriela Kadlecová Jovita Lukasik Martin Pilát Petra Vidnerová Mahmoud Safari Roman Neruda Frank Hutter GNN OOD 104 2 0 25 Apr 2024
ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing Kiran Madhusudhanan Gunnar Behrens Maximilian Stubbemann Lars Schmidt-Thieme 59 0 0 06 Mar 2024
Embracing Uncertainty Flexibility: Harnessing a Supervised Tree Kernel to Empower Ensemble Modelling for 2D Echocardiography-Based Prediction of Right Ventricular Volume T. A. Bohoran P. Kampaktsis Laura McLaughlin Jay Leb Gerry P. McCann A. Giannakidis 77 1 0 04 Mar 2024
Offensive Lineup Analysis in Basketball with Clustering Players Based on Shooting Style and Offensive Role Kazuhiro Yamada Keisuke Fujii 21 0 0 04 Mar 2024
Simulation Based Bayesian Optimization Roi Naveiro Becky Tang 49 0 0 19 Jan 2024
A tree-based varying coefficient model Henning Zakrisson Mathias Lindholm 89 1 0 11 Jan 2024
Robust Calibration For Improved Weather Prediction Under Distributional Shift Sankalp Gilda Neel Bhandari Wendy Mak Andrea Panizza UQCV OOD 21 1 0 08 Jan 2024
Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks Longze Li Jiang Chang Aleksandar Vakanski Yachun Wang Tiankai Yao Min Xian AI4CE 42 21 0 04 Nov 2023
Model Uncertainty based Active Learning on Tabular Data using Boosted Trees Sharath M Shankaranarayana 74 0 0 30 Oct 2023
Ensemble-based Hybrid Optimization of Bayesian Neural Networks and Traditional Machine Learning Algorithms Peiwen Tan BDL 97 1 0 09 Oct 2023
Using causal inference to avoid fallouts in data-driven parametric analysis: a case study in the architecture, engineering, and construction industry Xia Chen Ruiji Sun U. Saluz S. Schiavon Philipp Geyer 52 8 0 11 Sep 2023
Uncertainty and Explainable Analysis of Machine Learning Model for Reconstruction of Sonic Slowness Logs Hua Wang Yuqiong Wu Yushun Zhang F. Lai Zhou Feng Bing Xie Ailin Zhao 21 3 0 24 Aug 2023
ASDL: A Unified Interface for Gradient Preconditioning in PyTorch Kazuki Osawa Satoki Ishikawa Rio Yokota Shigang Li Torsten Hoefler ODL 87 15 0 08 May 2023
Modelling the performance of delivery vehicles across urban micro-regions to accelerate the transition to cargo-bike logistics Max Schrader Navish Kumar Nicolas Collignon Esben Sørig Soon-Jo Yoon Akash Srivastava Kai Xu Maria Astefanoaei 20 0 0 30 Jan 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 88 13 0 27 Jan 2023
A Robust Hypothesis Test for Tree Ensemble Pruning Daniel de Marchi Matthew Welch Michael R. Kosorok 22 1 0 24 Jan 2023
Scalable Estimation for Structured Additive Distributional Regression Nikolaus Umlauf Johannes Seiler Mattias Wetscher T. Simon S. Lang Nadja Klein 29 6 0 13 Jan 2023
ExcelFormer: A neural network surpassing GBDTs on tabular data Jintai Chen Jiahuan Yan Qiyuan Chen Danny Chen Jian Wu Jimeng Sun LMTD 161 27 0 07 Jan 2023
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS Gary Tom Riley J. Hickman Aniket N. Zinzuwadia A. Mohajeri Benjamín Sánchez-Lengeling A. Aspuru‐Guzik 75 16 0 03 Dec 2022
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty Yugo Fujimotol Kei Nakagawa Kentaro Imajo Kentaro Minami AIFin 68 3 0 31 Oct 2022
Nonparametric Probabilistic Regression with Coarse Learners B. Lucena 40 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 80 0 0 18 Oct 2022
Multi-Target XGBoostLSS Regression Alexander März 63 5 0 13 Oct 2022
TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method Jiaqi Luo Zihao Wei Junkai Man Shi-qian Xu 67 8 0 28 Sep 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network T. Kanazawa Chetan Gupta UQCV 79 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 84 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 68 59 0 16 Jun 2022
TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression Patryk Wielopolski Maciej Ziȩba UQCV 74 1 0 08 Jun 2022
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees Jonathan Brophy Daniel Lowd 72 10 0 23 May 2022
Probabilistic Models for Manufacturing Lead Times Recep Yusuf Bekci Yacine Mahdid Jinling Xing Nikita Letov Ying Zhang Zahid Pasha 57 0 0 28 Apr 2022
Distributional Gradient Boosting Machines Alexander März Thomas Kneib AI4CE 64 7 0 02 Apr 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization Jungtaek Kim Seungjin Choi 53 6 0 22 Feb 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 48 7 0 09 Nov 2021