80 citations · 148 across the 7 of their papers we have counts for
6 papers
XTab: Cross-table Pretraining for Tabular Transformers
Bingzhao Zhu, Xingjian Shi, Nick Erickson +3
The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-su…
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation
Jiaxin Cheng, Xiao Liang, Xingjian Shi +3
Layout-to-image generation refers to the task of synthesizing photo-realistic images based on semantic layouts. In this paper, we propose LayoutDiffuse that adapts a foundational d…
Removing Batch Normalization Boosts Adversarial Training
Haotao Wang, Aston Zhang, Shuai Zheng +3
Adversarial training (AT) defends deep neural networks against adversarial attacks. One challenge that limits its practical application is the performance degradation on clean samp…
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Hybrid methods that utilize both content and rating information are commonly used in many recommender systems. However, most of them use either handcrafted features or the bag-of-w…
Natural-Parameter Networks: A Class of Probabilistic Neural Networks
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Neural networks (NN) have achieved state-of-the-art performance in various applications. Unfortunately in applications where training data is insufficient, they are often prone to…
Dynamic Key-Value Memory Networks for Knowledge Tracing
Jiani Zhang, Xingjian Shi, Irwin King +1
Knowledge Tracing (KT) is a task of tracing evolving knowledge state of students with respect to one or more concepts as they engage in a sequence of learning activities. One impor…