Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour

31 January 2023

Papers citing "Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour"

11 / 11 papers shown

Title
Causal Discovery from Conditionally Stationary Time Series Carles Balsells-Rodas Ruibo Tu Tanmayee Narendra Yingzhen Li Gabriele Schweikert Hedvig Kjellström Yingzhen Li AI4TS BDL CML 126 6 0 12 Oct 2021
Neural Additive Vector Autoregression Models for Causal Discovery in Time Series Bart Bussmann Jannes Nys Steven Latré CML BDL 35 25 0 19 Oct 2020
One Thousand and One Hours: Self-driving Motion Prediction Dataset J. Houston G. Zuidhof Luca Bergamini Yawei Ye Long Chen Ashesh Jain Sammy Omari V. Iglovikov Peter Ondruska 87 367 0 25 Jun 2020
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference Chengxi Li Stanley H. Chan Yi-Ting Chen CML 134 51 0 05 Mar 2020
CLEVRER: CoLlision Events for Video REpresentation and Reasoning Kexin Yi Yuta Saito Yunzhu Li Pushmeet Kohli Jiajun Wu Antonio Torralba J. Tenenbaum NAI 118 473 0 03 Oct 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models Erdun Gao Kun Zhang Biwei Huang Clark Glymour CML AI4TS 62 64 0 26 May 2019
Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes Erdun Gao Kun Zhang Jiji Zhang Joseph Ramsey Ruben Sanchez-Romero Clark Glymour Bernhard Schölkopf 62 228 0 05 Mar 2019
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems R. Krajewski Julian Bock Laurent Kloeker L. Eckstein 82 994 0 11 Oct 2018
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 115 3,982 0 27 Feb 2013
Kernel-based Conditional Independence Test and Application in Causal Discovery Kun Zhang J. Peters Dominik Janzing Bernhard Schölkopf BDL CML 102 629 0 14 Feb 2012
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model Shohei Shimizu Takanori Inazumi Yasuhiro Sogawa Aapo Hyvarinen Yoshinobu Kawahara Takashi Washio P. Hoyer K. Bollen CML 102 511 0 13 Jan 2011