60 citations · 124 across the 19 of their papers we have counts for
5 papers · 1 filter
Simplicial 2-Complex Convolutional Neural Nets
Eric Bunch, Qian You, Glenn Fung +1
Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph. While useful, graph structure…
Flow-based Generative Models for Learning Manifold to Manifold Mappings
Xingjian Zhen, Rudrasis Chakraborty, Liu Yang +1
Many measurements or observations in computer vision and machine learning manifest as non-Euclidean data. While recent proposals (like spherical CNN) have extended a number of deep…
Online Graph Completion: Multivariate Signal Recovery in Computer Vision
Won Hwa Kim, Mona Jalal, Seongjae Hwang +2
The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision)…
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
Yunyang Xiong, Hanxiao Liu, Suyog Gupta +7
Inverted bottleneck layers, which are built upon depthwise convolutions, have been the predominant building blocks in state-of-the-art object detection models on mobile devices. In…
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret
Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi +1
Algorithmic decision making based on computer vision and machine learning technologies continue to permeate our lives. But issues related to biases of these models and the extent t…