activity
20222024
most citedFederated Self-Supervised Contrastive Learning and Masked Autoencoder for Dermatological Disease Diagnosis

3 citations · 5 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2024

PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud

Zhepeng Wang, Yi Sheng, Nirajan Koirala +4

Benefiting from cloud computing, today's early-stage quantum computers can be remotely accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it poses a hi…

cs.LG2023

Edge-InversionNet: Enabling Efficient Inference of InversionNet on Edge Devices

Zhepeng Wang, Isaacshubhanand Putla, Weiwen Jiang +1

Seismic full waveform inversion (FWI) is a widely used technique in geophysics for inferring subsurface structures from seismic data. And InversionNet is one of the most successful…

quant-ph20231 cited

A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices

Jinyang Li, Zhepeng Wang, Zhirui Hu +3

Quantum computing presents a promising approach for machine learning with its capability for extremely parallel computation in high-dimension through superposition and entanglement…

quant-ph20231 cited

VENUS: A Geometrical Representation for Quantum State Visualization

Shaolun Ruan, Ribo Yuan, Qiang Guan +6

Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widel…

cs.LG20223 cited

Federated Self-Supervised Contrastive Learning and Masked Autoencoder for Dermatological Disease Diagnosis

Yawen Wu, Dewen Zeng, Zhepeng Wang +5

In dermatological disease diagnosis, the private data collected by mobile dermatology assistants exist on distributed mobile devices of patients. Federated learning (FL) can use de…

eess.IV2022

Distributed Contrastive Learning for Medical Image Segmentation

Yawen Wu, Dewen Zeng, Zhepeng Wang +2

Supervised deep learning needs a large amount of labeled data to achieve high performance. However, in medical imaging analysis, each site may only have a limited amount of data an…