most citedSHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

5 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20205 cited

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

Hao-Zhe Feng, Kezhi Kong, Minghao Chen +3

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference r…

cs.LG2020

KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation

Hao-Zhe Feng, Zhaoyang You, Minghao Chen +5

Conventional unsupervised multi-source domain adaptation (UMDA) methods assume all source domains can be accessed directly. This neglects the privacy-preserving policy, that is, al…

cs.HC2020

GraphFederator: Federated Visual Analysis for Multi-party Graphs

Dongming Han, Wei Chen, Rusheng Pan +8

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs. Inspired by…

cs.SE2020

A Systematic Literature Review of Modern Software Visualization

Noptanit Chotisarn, Leonel Merino, Xu Zheng +4

We report on the state-of-the-art of software visualization. To ensure reproducibility, we adopted the Systematic Literature Review methodology. That is, we analyzed 1440 entries f…

cs.LG20191 cited

An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE

Tianye Zhang, Haozhe Feng, Zexian Chen +4

Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid. Identifying insights helps analysts understand the…