6 citations · 11 across the 2 of their papers we have counts for
5 papers
APSNet: Attention Based Point Cloud Sampling
Yang Ye, Xiulong Yang, Shihao Ji
Processing large point clouds is a challenging task. Therefore, the data is often downsampled to a smaller size such that it can be stored, transmitted and processed more efficient…
JEM++: Improved Techniques for Training JEM
Xiulong Yang, Shihao Ji
Joint Energy-based Model (JEM) is a recently proposed hybrid model that retains strong discriminative power of modern CNN classifiers, while generating samples rivaling the quality…
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More
Xiulong Yang, Hui Ye, Yang Ye +2
Joint Energy-based Model (JEM) of Grathwohl et al. shows that a standard softmax classifier can be reinterpreted as an energy-based model (EBM) for the joint distribution p(x,y); t…
A Unified Plug-and-Play Framework for Effective Data Denoising and Robust Abstention
Krishanu Sarker, Xiulong Yang, Yang Li +2
The success of Deep Neural Networks (DNNs) highly depends on data quality. Moreover, predictive uncertainty makes high performing DNNs risky for real-world deployment. In this pape…
Learning with Multiplicative Perturbations
Xiulong Yang, Shihao Ji
Adversarial Training (AT) and Virtual Adversarial Training (VAT) are the regularization techniques that train Deep Neural Networks (DNNs) with adversarial examples generated by add…