9 citations · 11 across the 7 of their papers we have counts for
7 papers
Multi-convex Programming for Discrete Latent Factor Models Prototyping
Hao Zhu, Shengchao Yan, Jasper Hoffmann +1
Discrete latent factor models (DLFMs) are widely used in various domains such as machine learning, economics, neuroscience, psychology, etc. Currently, fitting a DLFM to some datas…
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding
Chenguang Huang, Shengchao Yan, Wolfram Burgard
Dynamic scene understanding remains a persistent challenge in robotic applications. Early dynamic mapping methods focused on mitigating the negative influence of short-term dynamic…
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
Yue Yao, Shengchao Yan, Daniel Goehring +2
Robustness against Out-of-Distribution (OoD) samples is a key performance indicator of a trajectory prediction model. However, the development and ranking of state-of-the-art (SotA…
Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Driving
Shengchao Yan, Lukas König, Wolfram Burgard
Active traffic management with autonomous vehicles offers the potential for reduced congestion and improved traffic flow. However, developing effective algorithms for real-world sc…
Learning Continuous Control with Geometric Regularity from Robot Intrinsic Symmetry
Shengchao Yan, Baohe Zhang, Yuan Zhang +2
Geometric regularity, which leverages data symmetry, has been successfully incorporated into deep learning architectures such as CNNs, RNNs, GNNs, and Transformers. While this conc…
Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning
Shengchao Yan, Tim Welschehold, Daniel Büscher +1
The transition from today's mostly human-driven traffic to a purely automated one will be a gradual evolution, with the effect that we will likely experience mixed traffic in the n…
Efficiency and Equity are Both Essential: A Generalized Traffic Signal Controller with Deep Reinforcement Learning
Shengchao Yan, Jingwei Zhang, Daniel Büscher +1
Traffic signal controllers play an essential role in today's traffic system. However, the majority of them currently is not sufficiently flexible or adaptive to generate optimal tr…