Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach

29 November 2023

Papers citing "Exploring Factors Affecting Pedestrian Crash Severity Using TabNet: A Deep Learning Approach"

9 / 9 papers shown

Title
Exploring the Determinants of Pedestrian Crash Severity Using an AutoML Approach Amir Rafe Patrick A. Singleton 30 2 0 07 Jun 2024
Inferring Heterogeneous Treatment Effects of Crashes on Highway Traffic: A Doubly Robust Causal Machine Learning Approach Shuang Li Ziyuan Pu Zhiyong Cui Seunghyeon Lee Xiucheng Guo D. Ngoduy CML 40 12 0 01 Jan 2024
Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities Zhaoyi Xu J. Saleh 49 343 0 19 Aug 2020
TabNet: Attentive Interpretable Tabular Learning Sercan O. Arik Tomas Pfister LMTD 118 1,314 0 20 Aug 2019
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 367 5,714 0 25 Jul 2019
Consistent Individualized Feature Attribution for Tree Ensembles Scott M. Lundberg G. Erion Su-In Lee FAtt TDI 55 1,379 0 12 Feb 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 606 21,613 0 22 May 2017
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 381 37,815 0 09 Mar 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 272 25,443 0 09 Jun 2011