ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2205.11412
  4. Cited By
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression
  Trees
v1v2 (latest)

Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees

23 May 2022
Jonathan Brophy
Daniel Lowd
ArXiv (abs)PDFHTMLGithub (31★)

Papers citing "Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees"

14 / 14 papers shown
Title
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing,
  and Improving Uncertainty Quantification
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification
Youngseog Chung
I. Char
Han Guo
J. Schneider
Willie Neiswanger
72
71
0
21 Sep 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free
  Uncertainty Quantification
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Anastasios Nikolas Angelopoulos
Stephen Bates
OOD
204
622
0
15 Jul 2021
TREX: Tree-Ensemble Representer-Point Explanations
TREX: Tree-Ensemble Representer-Point Explanations
Jonathan Brophy
Daniel Lowd
TDI
50
7
0
11 Sep 2020
Uncertainty in Gradient Boosting via Ensembles
Uncertainty in Gradient Boosting via Ensembles
Aleksei Ustimenko
Liudmila Prokhorenkova
A. Malinin
UQCV
71
95
0
18 Jun 2020
SGLB: Stochastic Gradient Langevin Boosting
SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko
Liudmila Prokhorenkova
59
19
0
20 Jan 2020
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series
  Forecasting
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
Bryan Lim
Sercan O. Arik
Nicolas Loeff
Tomas Pfister
AI4TS
118
1,463
0
19 Dec 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PERUD
244
1,415
0
21 Oct 2019
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan
Anand Avati
D. Ding
Khanh K. Thai
S. Basu
A. Ng
Alejandro Schuler
BDL
34
302
0
08 Oct 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical
  XAI
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
Erico Tjoa
Cuntai Guan
XAI
106
1,447
0
17 Jul 2019
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer
  on Time Series Forecasting
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Shiyang Li
Xiaoyong Jin
Yao Xuan
Xiyou Zhou
Wenhu Chen
Yu Wang
Xifeng Yan
AI4TS
107
1,420
0
29 Jun 2019
Deep Factors for Forecasting
Deep Factors for Forecasting
Bernie Wang
Alex Smola
Danielle C. Maddix
Jan Gasthaus
Dean Phillips Foster
Tim Januschowski
BDL
77
174
0
28 May 2019
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas
Valentin Flunkert
Jan Gasthaus
AI4TSUQCVBDL
81
2,112
0
13 Apr 2017
The Random Forest Kernel and other kernels for big data from random
  partitions
The Random Forest Kernel and other kernels for big data from random partitions
Alex O. Davies
Zoubin Ghahramani
156
66
0
18 Feb 2014
A tutorial on conformal prediction
A tutorial on conformal prediction
Glenn Shafer
V. Vovk
452
1,144
0
21 Jun 2007
1