17 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.CV2019
End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition
Shaofei Wang, Vishnu Lokhande, Maneesh Singh +2
Modern computer vision (CV) is often based on convolutional neural networks (CNNs) that excel at hierarchical feature extraction. The previous generation of CV approaches was often…
cs.CV2019
Wavelets to the Rescue: Improving Sample Quality of Latent Variable Deep Generative Models
Prashnna K Gyawali, Rudra Saha, Linwei Wang +2
Variational Autoencoders (VAE) are probabilistic deep generative models underpinned by elegant theory, stable training processes, and meaningful manifold representations. However,…
cs.LG2017★ 17 cited
Lipschitz Properties for Deep Convolutional Networks
Radu Balan, Maneesh Singh, Dongmian Zou
In this paper we discuss the stability properties of convolutional neural networks. Convolutional neural networks are widely used in machine learning. In classification they are ma…