activity
20182023
most citedMaximum Density Divergence for Domain Adaptation

343 citations · 805 across the 37 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023

iBARLE: imBalance-Aware Room Layout Estimation

Taotao Jing, Lichen Wang, Naji Khosravan +4

Room layout estimation predicts layouts from a single panorama. It requires datasets with large-scale and diverse room shapes to train the models. However, there are significant im…

cs.CV2023

Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation

Janet Wang, Yunbei Zhang, Zhengming Ding +1

The development of reliable and fair diagnostic systems is often constrained by the scarcity of labeled data. To address this challenge, our work explores the feasibility of unsupe…

q-bio.NC2023★ 3 cited

Angle Basis: a Generative Model and Decomposition for Functional Connectivity

Anton Orlichenko, Gang Qu, Ziyu Zhou +2

Functional connectivity (FC) is one of the most common inputs to fMRI-based predictive models, due to a combination of its simplicity and robustness. However, there may be a lack o…

cs.LG2023

CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data

Chen Zhao, Anqi Liu, Xiao Zhang +6

Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data. Each omics technique only provides a limited vi…

cs.CV2023

IDA: Informed Domain Adaptive Semantic Segmentation

Zheng Chen, Zhengming Ding, Jason M. Gregory +1

Mixup-based data augmentation has been validated to be a critical stage in the self-training framework for unsupervised domain adaptive semantic segmentation (UDA-SS), which aims t…

cs.CV2023

Visualizing Transferred Knowledge: An Interpretive Model of Unsupervised Domain Adaptation

Wenxiao Xiao, Zhengming Ding, Hongfu Liu

Many research efforts have been committed to unsupervised domain adaptation (DA) problems that transfer knowledge learned from a labeled source domain to an unlabeled target domain…