5 citations · 16 across the 8 of their papers we have counts for
8 papers
Other Vehicle Trajectories Are Also Needed: A Driving World Model Unifies Ego-Other Vehicle Trajectories in Video Latent Space
Jian Zhu, Zhengyu Jia, Tian Gao +6
Advanced end-to-end autonomous driving systems predict other vehicles' motions and plan ego vehicle's trajectory. The world model that can foresee the outcome of the trajectory has…
CO2: Efficient Distributed Training with Full Communication-Computation Overlap
Weigao Sun, Zhen Qin, Weixuan Sun +5
The fundamental success of large language models hinges upon the efficacious implementation of large-scale distributed training techniques. Nevertheless, building a vast, high-perf…
Sampled Transformer for Point Sets
Shidi Li, Christian Walder, Alexander Soen +2
The sparse transformer can reduce the computational complexity of the self-attention layers to , whilst still being a universal approximator of continuous sequence-to-sequenc…
SPA-VAE: Similar-Parts-Assignment for Unsupervised 3D Point Cloud Generation
Shidi Li, Christian Walder, Miaomiao Liu
This paper addresses the problem of unsupervised parts-aware point cloud generation with learned parts-based self-similarity. Our SPA-VAE infers a set of latent canonical candidate…
EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation
Shidi Li, Miaomiao Liu, Christian Walder
This paper tackles the problem of parts-aware point cloud generation. Unlike existing works which require the point cloud to be segmented into parts a priori, our parts-aware editi…
Interval-censored Hawkes processes
Marian-Andrei Rizoiu, Alexander Soen, Shidi Li +4
Interval-censored data solely records the aggregated counts of events during specific time intervals - such as the number of patients admitted to the hospital or the volume of vehi…
Robot Playing Kendama with Model-Based and Model-Free Reinforcement Learning
Shidi Li
Several model-based and model-free methods have been proposed for the robot trajectory learning task. Both approaches have their benefits and drawbacks. They can usually complement…
Smooth and Efficient Policy Exploration for Robot Trajectory Learning
Shidi Li, Chee-Meng Chew, Velusamy Subramaniam
Many policy search algorithms have been proposed for robot learning and proved to be practical in real robot applications. However, there are still hyperparameters in the algorithm…