187 citations · 1.3k across the 43 of their papers we have counts for
8 papers · 1 filter
Recurrent Attentive Neural Process for Sequential Data
Shenghao Qin, Jiacheng Zhu, Jimmy Qin +2
Neural processes (NPs) learn stochastic processes and predict the distribution of target output adaptively conditioned on a context set of observed input-output pairs. Furthermore,…
Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process
Jiacheng Zhu, Shenghao Qin, Wenshuo Wang +1
Predicting surrounding vehicle behaviors are critical to autonomous vehicles when negotiating in multi-vehicle interaction scenarios. Most existing approaches require tedious train…
Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression
Weiyang Zhang, Wenshuo Wang, Ding Zhao
Generating multi-vehicle interaction scenarios can benefit motion planning and decision making of autonomous vehicles when on-road data is insufficient. This paper presents an effi…
Measuring Similarity of Interactive Driving Behaviors Using Matrix Profile
Qin Lin, Wenshuo Wang, Yihuan Zhang +1
Understanding multi-vehicle interactive behaviors with temporal sequential observations is crucial for autonomous vehicles to make appropriate decisions in an uncertain traffic env…
Active Learning for Risk-Sensitive Inverse Reinforcement Learning
Rui Chen, Wenshuo Wang, Zirui Zhao +1
One typical assumption in inverse reinforcement learning (IRL) is that human experts act to optimize the expected utility of a stochastic cost with a fixed distribution. This assum…
A General Framework of Learning Multi-Vehicle Interaction Patterns from Videos
Chengyuan Zhang, Jiacheng Zhu, Wenshuo Wang +1
Semantic learning and understanding of multi-vehicle interaction patterns in a cluttered driving environment are essential but challenging for autonomous vehicles to make proper de…
Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
Yaohui Guo, Vinay Varma Kalidindi, Mansur Arief +4
Autonomous vehicles are expected to navigate in complex traffic scenarios with multiple surrounding vehicles. The correlations between road users vary over time, the degree of whic…
Metropolized Knockoff Sampling
Stephen Bates, Emmanuel Candès, Lucas Janson +1
Model-X knockoffs is a wrapper that transforms essentially any feature importance measure into a variable selection algorithm, which discovers true effects while rigorously control…