9 citations · 12 across the 4 of their papers we have counts for
4 papers
Unrolling Graph-based Douglas-Rachford Algorithm for Image Interpolation with Informed Initialization
Xue Zhang, Bingshuo Hu, Gene Cheung
Conventional deep neural nets (DNNs) initialize network parameters at random and then optimize each one via stochastic gradient descent (SGD), resulting in substantial risk of poor…
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
Haotian Xue, Alexandre Araujo, Bin Hu +1
Neural networks are known to be susceptible to adversarial samples: small variations of natural examples crafted to deliberately mislead the models. While they can be easily genera…
A Unified Algebraic Perspective on Lipschitz Neural Networks
Alexandre Araujo, Aaron Havens, Blaise Delattre +2
Important research efforts have focused on the design and training of neural networks with a controlled Lipschitz constant. The goal is to increase and sometimes guarantee the robu…
Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation
Kai Ye, Yinru Ye, Minqiang Yang +1
The main challenges of image-to-image (I2I) translation are to make the translated image realistic and retain as much information from the source domain as possible. To address thi…