Publications

2023

[20] Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics
      Brian R Bartoldson, Yeping Hu, Amar Saini, Jose Cadena, Yucheng Fu, Jie Bao, Zhijie Xu, Brenda Ng, and Phan Nguyen
      2023 International Conference on Learning Representations (ICLR), Workshop on Physics for Machine Learning [paper]

[19] Predicting Fluid Dynamics in Physical-informed Mesh-reduced Space
      Yeping Hu, Bo Lei, and Victor M. Castillo
      2023 International Conference on Learning Representations (ICLR), Workshop on Physics for Machine Learning [paper]

[18] Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation
       Wei-Jer Chang, Chen Tang, Chenran Li, Yeping Hu, Masayoshi Tomizuka, and Wei Zhan
     2023 (in submission) [paper]

2022

[17] Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction
      Yeping Hu, Wei Zhan, and Masayoshi Tomizuka
      2022 IEEE Transactions on Intelligent Transportation Systems (T-ITS) [paper]

[16] Generalizability Analysis of Graph-based Trajectory Predictor with Vectorized Representation
     Juanwu Lu, Wei Zhan, Masayoshi Tomizuka, and Yeping Hu
     2022 IEEE International Conference on Robotics and Automation (IROS) [paper]

[15] Analyzing and Enhancing Closed-loop Stability in Reactive Simulation
     Wei-Jer Chang, Yeping Hu, Chenran Li, Wei Zhan, and Masayoshi Tomizuka
     2022 IEEE International Conference on Intelligent Transportation Systems (ITSC) [paper]

[14] Causal-based Time Series Domain Generalization for Vehicle Intention Prediction
     Yeping Hu, Xiaogang Jia, Masayoshi Tomizuka, and Wei Zhan
     2022 IEEE International Conference on Robotics and Automation (ICRA) [paper]

[13] Online Adaptation of Neural Network Models by Modified Extended Kalman Filter for Customizable and Transferable Driving Behavior Prediction
     Letian Wang, Yeping Hu, and Changliu Liu
     2022 AAAI Conference on Artificial Intelligence, Workshop on Human-Centric Self-Supervised Learning [paper]

[12] Transferable and Adaptable Driving Behavior Prediction
     Letian Wang, Yeping Hu, Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Changliu Liu
     2022 (in submission) [arXiv]

2021

[11] Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction
     Letian Wang, Yeping Hu,  Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Changliu Liu
     2021 NeurIPS Conference on Neural Information Processing Systems, Workshop on Machine Learning or Autonomous Driving [paper] (Spotlight Talk)

[10] Causal-based Time Series Domain Generalization for Vehicle Intention Prediction
     Yeping Hu, Xiaogang Jia, Masayoshi Tomizuka, and Wei Zhan
     2021 NeurIPS Conference on Neural Information Processing Systems, Workshop on Distribution Shifts [paper]

2019

[9]  Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios
      Yeping Hu, Alireza Nakhaei, Masayoshi Tomizuka, and Kikuo Fujimura
      2019 IEEE International Conference on Intelligent Robots and Systems (IROS) (Best Paper Award Finalist) [paper][video]

[8] Generic Prediction Architecture Considering both Rational and Irrational Driving Behaviors
      Yeping Hu, Liting Sun, and Masayoshi Tomizuka
      2019 IEEE Intelligent Transportation Systems (ITSC) [paper]

[7] Interpretable Modeling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
      Liting Sun, Wei Zhan, Yeping Hu, and Masayoshi Tomizuka
      2019 IEEE Intelligent Transportation Systems (ITSC) [paper]

[6] Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model
      Yeping Hu, Wei Zhan, Liting Sun, and Masayoshi Tomizuka
      2019 IEEE Intelligent Vehicles Symposium (IV) [paper]

2018

[5] Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
      Jiachen Li, Wei Zhan, Yeping Hu, and Masayoshi Tomizuka
      2018 IEEE Transactions on Intelligent Transportation Systems (T-ITS) [paper]

[4] Probabilistic Prediction of Vehicle Semantic Intention and Motion
      Yeping Hu, Wei Zhan, and Masayoshi Tomizuka
      2018 IEEE Intelligent Vehicles Symposium (IV) (Best Student Paper) [paper][video]

[3] A Framework for Probabilistic Generic Traffic Scene Prediction
      Yeping Hu, Wei Zhan, and Masayoshi Tomizuka
      2018 IEEE Intelligent Transportation Systems (ITSC) [paper]

[2] Towards a Fatality-aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios
      Wei Zhan, Liting Sun, Yeping Hu, Jiachen Li, and Masayoshi Tomizuka
      2018 IEEE Intelligent Transportation Systems (ITSC) [paper]

2017

[1] Safe and Feasible Motion Generation for Autonomous Driving via Constrained Policy Net
      Wei Zhan, Jiachen Li, Yeping Hu, and Masayoshi Tomizuka
      2017 IEEE Industrial Electronic Society (IES) [paper]