33 citations · 178 across the 28 of their papers we have counts for
11 papers · 1 filter
M-EBM: Towards Understanding the Manifolds of Energy-Based Models
Xiulong Yang, Shihao Ji
Energy-based models (EBMs) exhibit a variety of desirable properties in predictive tasks, such as generality, simplicity and compositionality. However, training EBMs on high-dimens…
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…
Towards Bridging the Performance Gaps of Joint Energy-based Models
Xiulong Yang, Qing Su, Shihao Ji
Can we train a hybrid discriminative-generative model within a single network? This question has recently been answered in the affirmative, introducing the field of Joint Energy-ba…
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Xiulong Yang, Sheng-Min Shih, Yinlin Fu +2
Diffusion Denoising Probability Models (DDPM) and Vision Transformer (ViT) have demonstrated significant progress in generative tasks and discriminative tasks, respectively, and th…
ChiTransformer:Towards Reliable Stereo from Cues
Qing Su, Shihao Ji
Current stereo matching techniques are challenged by restricted searching space, occluded regions and sheer size. While single image depth estimation is spared from these challenge…
Generative Dynamic Patch Attack
Xiang Li, Shihao Ji
Adversarial patch attack is a family of attack algorithms that perturb a part of image to fool a deep neural network model. Existing patch attacks mostly consider injecting adversa…
Reducing Risk and Uncertainty of Deep Neural Networks on Diagnosing COVID-19 Infection
Krishanu Sarker, Sharbani Pandit, Anupam Sarker +2
Effective and reliable screening of patients via Computer-Aided Diagnosis can play a crucial part in the battle against COVID-19. Most of the existing works focus on developing sop…
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…
Neural Image Compression and Explanation
Xiang Li, Shihao Ji
Explaining the prediction of deep neural networks (DNNs) and semantic image compression are two active research areas of deep learning with a numerous of applications in decision-c…
Towards Robust Human Activity Recognition from RGB Video Stream with Limited Labeled Data
Krishanu Sarker, Mohamed Masoud, Saeid Belkasim +1
Human activity recognition based on video streams has received numerous attentions in recent years. Due to lack of depth information, RGB video based activity recognition performs…
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks
Xiang Li, Shihao Ji
Deep neural networks (DNNs) have been enormously successful across a variety of prediction tasks. However, recent research shows that DNNs are particularly vulnerable to adversaria…