activity
20182020
most citedUnsupervised Object Segmentation with Explicit Localization Module

4 citations · 4 across the 1 of their papers we have counts for

collaborators

11 papers

cs.LG2020

Energy-based Out-of-distribution Detection

Weitang Liu, Xiaoyun Wang, John D. Owens +1

Determining whether inputs are out-of-distribution (OOD) is an essential building block for safely deploying machine learning models in the open world. However, previous methods re…

cs.DC2020

Fast Gunrock Subgraph Matching (GSM) on GPUs

Leyuan Wang, John D. Owens

In this paper, we propose a GPU-efficient subgraph isomorphism algorithm using the Gunrock graph analytic framework, GSM (Gunrock Subgraph Matching), to compute graph matching on G…

cs.CV20194 cited

Unsupervised Object Segmentation with Explicit Localization Module

Weitang Liu, Lifeng Wei, James Sharpnack +1

In this paper, we propose a novel architecture that iteratively discovers and segments out the objects of a scene based on the image reconstruction quality. Different from other ap…

cs.DC2019

RDMA vs. RPC for Implementing Distributed Data Structures

Benjamin Brock, Yuxin Chen, Jiakun Yan +3

Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distr…

cs.DC2019

Fast BFS-Based Triangle Counting on GPUs

Leyuan Wang, John D. Owens

In this paper, we propose a novel method to compute triangle counting on GPUs. Unlike previous formulations of graph matching, our approach is BFS-based by traversing the graph in…

cs.CV2018

Object Localization with a Weakly Supervised CapsNet

Weitang Liu, Emad Barsoum, John D. Owens

Inspired by CapsNet's routing-by-agreement mechanism with its ability to learn object properties, we explore if those properties in turn can determine new properties of the objects…