63 citations · 102 across the 14 of their papers we have counts for
14 papers
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models
Yan Xie, Zequn Zeng, Hao Zhang +5
Concept Bottleneck Models (CBMs) try to make the decision-making process transparent by exploring an intermediate concept space between the input image and the output prediction. E…
Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks
Chaojie Wang, Xinyang Liu, Dongsheng Wang +3
Although existing variational graph autoencoders (VGAEs) have been widely used for modeling and generating graph-structured data, most of them are still not flexible enough to appr…
A Non-negative VAE:the Generalized Gamma Belief Network
Zhibin Duan, Tiansheng Wen, Muyao Wang +2
The gamma belief network (GBN), often regarded as a deep topic model, has demonstrated its potential for uncovering multi-layer interpretable latent representations in text data. I…
HICEScore: A Hierarchical Metric for Image Captioning Evaluation
Zequn Zeng, Jianqiao Sun, Hao Zhang +5
Image captioning evaluation metrics can be divided into two categories, reference-based metrics and reference-free metrics. However, reference-based approaches may struggle to eval…
MeaCap: Memory-Augmented Zero-shot Image Captioning
Zequn Zeng, Yan Xie, Hao Zhang +3
Zero-shot image captioning (IC) without well-paired image-text data can be divided into two categories, training-free and text-only-training. Generally, these two types of methods…
SnapCap: Efficient Snapshot Compressive Video Captioning
Jianqiao Sun, Yudi Su, Hao Zhang +5
Video Captioning (VC) is a challenging multi-modal task since it requires describing the scene in language by understanding various and complex videos. For machines, the traditiona…
ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based Polishing
Zequn Zeng, Hao Zhang, Zhengjue Wang +3
Zero-shot capability has been considered as a new revolution of deep learning, letting machines work on tasks without curated training data. As a good start and the only existing o…
A Variational Edge Partition Model for Supervised Graph Representation Learning
Yilin He, Chaojie Wang, Hao Zhang +2
Graph neural networks (GNNs), which propagate the node features through the edges and learn how to transform the aggregated features under label supervision, have achieved great su…
A Prototype-Oriented Framework for Unsupervised Domain Adaptation
Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng +4
Existing methods for unsupervised domain adaptation often rely on minimizing some statistical distance between the source and target samples in the latent space. To avoid the sampl…
MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing
Zhengjue Wang, Hao Zhang, Ziheng Cheng +2
To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks a…
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference
Hao Zhang, Bo Chen, Yulai Cong +3
To build a flexible and interpretable model for document analysis, we develop deep autoencoding topic model (DATM) that uses a hierarchy of gamma distributions to construct its mul…
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling
Hao Zhang, Bo Chen, Long Tian +2
For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that int…
Deep Poisson gamma dynamical systems
Dandan Guo, Bo Chen, Hao Zhang +1
We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequentially observed multivariate count data, improving previously proposed models by not only mining deep hierarc…
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling
Hao Zhang, Bo Chen, Dandan Guo +1
To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid aut…