47 citations · 53 across the 7 of their papers we have counts for
7 papers
Expanding Versatility of Agile Locomotion through Policy Transitions Using Latent State Representation
Guilherme Christmann, Ying-Sheng Luo, Jonathan Hans Soeseno +1
This paper proposes the transition-net, a robust transition strategy that expands the versatility of robot locomotion in the real-world setting. To this end, we start by distributi…
Transition Motion Tensor: A Data-Driven Approach for Versatile and Controllable Agents in Physically Simulated Environments
Jonathan Hans Soeseno, Ying-Sheng Luo, Trista Pei-Chun Chen +1
This paper proposes the Transition Motion Tensor, a data-driven framework that creates novel and physically accurate transitions outside of the motion dataset. It enables simulated…
A Dense Tensor Accelerator with Data Exchange Mesh for DNN and Vision Workloads
Yu-Sheng Lin, Wei-Chao Chen. Chia-Lin Yang, Shao-Yi Chien
We propose a dense tensor accelerator called VectorMesh, a scalable, memory-efficient architecture that can support a wide variety of DNN and computer vision workloads. Its buildin…
TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions
Daniel Stanley Tan, Yi-Chun Chen, Trista Pei-Chun Chen +1
In this paper, we propose a framework called TrustMAE to address the problem of product defect classification. Instead of relying on defective images that are difficult to collect…
GrateTile: Efficient Sparse Tensor Tiling for CNN Processing
Yu-Sheng Lin, Hung Chang Lu, Yang-Bin Tsao +3
We propose GrateTile, an efficient, hardwarefriendly data storage scheme for sparse CNN feature maps (activations). It divides data into uneven-sized subtensors and, with small ind…
CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion
Ying-Sheng Luo, Jonathan Hans Soeseno, Trista Pei-Chun Chen +1
Motion synthesis in a dynamic environment has been a long-standing problem for character animation. Methods using motion capture data tend to scale poorly in complex environments b…
MERIT: Tensor Transform for Memory-Efficient Vision Processing on Parallel Architectures
Yu-Sheng Lin, Wei-Chao Chen, Shao-Yi Chien
Computationally intensive deep neural networks (DNNs) are well-suited to run on GPUs, but newly developed algorithms usually require the heavily optimized DNN routines to work effi…