activity
20202022
most citedDeep Random Forest with Ferroelectric Analog Content Addressable Memory

11 citations · 19 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022

SteppingNet: A Stepping Neural Network with Incremental Accuracy Enhancement

Wenhao Sun, Grace Li Zhang, Xunzhao Yin +4

Deep neural networks (DNNs) have successfully been applied in many fields in the past decades. However, the increasing number of multiply-and-accumulate (MAC) operations in DNNs pr…

cs.ET20225 cited

A Homogeneous Processing Fabric for Matrix-Vector Multiplication and Associative Search Using Ferroelectric Time-Domain Compute-in-Memory

Xunzhao Yin, Qingrong Huang, Franz Müller +8

In this work, we propose a ferroelectric FET(FeFET) time-domain compute-in-memory (TD-CiM) array as a homogeneous processing fabric for binary multiplication-accumulation (MAC) and…

cs.LG2022

Worst-Case Dynamic Power Distribution Network Noise Prediction Using Convolutional Neural Network

Xiao Dong, Yufei Chen, Xunzhao Yin +1

Worst-case dynamic PDN noise analysis is an essential step in PDN sign-off to ensure the performance and reliability of chips. However, with the growing PDN size and increasing sce…

cs.ET202111 cited

Deep Random Forest with Ferroelectric Analog Content Addressable Memory

Xunzhao Yin, Franz Müller, Ann Franchesca Laguna +14

Deep random forest (DRF), which incorporates the core features of deep learning and random forest (RF), exhibits comparable classification accuracy, interpretability, and low memor…

cs.LG20211 cited

Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation

Xuezhong Lin, Jingyu Pan, Jinming Xu +2

As technology scaling is approaching the physical limit, lithography hotspot detection has become an essential task in design for manufacturability. While the deployment of pattern…

cs.CV20202 cited

Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift

Qinming Zhang, Luyan Liu, Kai Ma +2

Deep convolutional neural networks (DCNNs) have contributed many breakthroughs in segmentation tasks, especially in the field of medical imaging. However, \textit{domain shift} and…