1 citations · 1 across the 5 of their papers we have counts for
5 papers
Accelerating Inference of Networks in the Frequency Domain
Chenqiu Zhao, Guanfang Dong, Anup Basu
It has been demonstrated that networks' parameters can be significantly reduced in the frequency domain with a very small decrease in accuracy. However, given the cost of frequency…
Deep Clustering via Distribution Learning
Guanfang Dong, Zijie Tan, Chenqiu Zhao +1
Distribution learning finds probability density functions from a set of data samples, whereas clustering aims to group similar data points to form clusters. Although there are deep…
Bridging Distribution Learning and Image Clustering in High-dimensional Space
Guanfang Dong, Chenqiu Zhao, Anup Basu
Distribution learning focuses on learning the probability density function from a set of data samples. In contrast, clustering aims to group similar objects together in an unsuperv…
Learning Distributions via Monte-Carlo Marginalization
Chenqiu Zhao, Guanfang Dong, Anup Basu
We propose a novel method to learn intractable distributions from their samples. The main idea is to use a parametric distribution model, such as a Gaussian Mixture Model (GMM), to…
Is Deep Learning Network Necessary for Image Generation?
Chenqiu Zhao, Guanfang Dong, Anup Basu
Recently, images are considered samples from a high-dimensional distribution, and deep learning has become almost synonymous with image generation. However, is a deep learning netw…