10 citations · 16 across the 7 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.LG2021★ 1 cited
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning
Xin Zhang, Zixuan Liu, Kaiwen Xiao +5
Labels are costly and sometimes unreliable. Noisy label learning, semi-supervised learning, and contrastive learning are three different strategies for designing learning processes…
cs.CL2021★ 2 cited
GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering
Weixin Liang, Yanhao Jiang, Zixuan Liu
Images are more than a collection of objects or attributes -- they represent a web of relationships among interconnected objects. Scene Graph has emerged as a new modality for a st…
eess.IV2021★ 1 cited
Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models
Zixuan Liu, Ehsan Adeli, Kilian M. Pohl +1
Interpretability is a critical factor in applying complex deep learning models to advance the understanding of brain disorders in neuroimaging studies. To interpret the decision pr…