4 papers
Dense Vision Transformer Compression with Few Samples
Hanxiao Zhang, Yifan Zhou, Guo-Hua Wang +1
Few-shot model compression aims to compress a large model into a more compact one with only a tiny training set (even without labels). Block-level pruning has recently emerged as a…
Autoencoder with Group-based Decoder and Multi-task Optimization for Anomalous Sound Detection
Yifan Zhou, Dongxing Xu, Haoran Wei +1
In industry, machine anomalous sound detection (ASD) is in great demand. However, collecting enough abnormal samples is difficult due to the high cost, which boosts the rapid devel…
Enhancing State Estimation in Robots: A Data-Driven Approach with Differentiable Ensemble Kalman Filters
Xiao Liu, Geoffrey Clark, Joseph Campbell +2
This paper introduces a novel state estimation framework for robots using differentiable ensemble Kalman filters (DEnKF). DEnKF is a reformulation of the traditional ensemble Kalma…
Learning Ball-balancing Robot Through Deep Reinforcement Learning
Yifan Zhou, Jianghao Lin, Shuai Wang +1
The ball-balancing robot (ballbot) is a good platform to test the effectiveness of a balancing controller. Considering balancing control, conventional model-based feedback control…