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Automating Artifact Detection in Video Games


Authors:  ParmidaDavarmanesh, KuanhaoJiang, TingtingOu....
Published date-11/30/2020

Abstract: In spite of advances in gaming hardware and software, gameplay is often tainted with graphics errors, glitches, and screen artifacts. This proof of concept study presents a machine learning approach …

UWB at SemEval-2020 Task 1: Lexical Semantic Change Detection


Authors:  OndřejPražák, PavelPřibáň, StephenTaylor....
Published date-11/30/2020

Abstract: In this paper, we describe our method for the detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora, …

Doubly Stochastic Subspace Clustering


Authors:  DerekLim, RenéVidal, BenjaminD.Haeffele....
Published date-11/30/2020
Tasks:  Clustering, ImageClustering

Abstract: Many state-of-the-art subspace clustering methods follow a two-step process by first constructing an affinity matrix between data points and then applying spectral clustering to this affinity. Most of the research …

Language-Driven Region Pointer Advancement for Controllable Image Captioning


Authors:  AnnikaLindh, RobertJ.Ross, JohnD.Kelleher....
Published date-11/30/2020
Tasks:  ImageCaptioning

Abstract: Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated …

Graph convolutions that can finally model local structure


Authors:  RémyBrossard, OrielFrigo, DavidDehaene....
Published date-11/30/2020

Abstract: Despite quick progress in the last few years, recent studies have shown that modern graph neural networks can still fail at very simple tasks, like detecting small cycles. This hints …

Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics


Authors:  RaghavKansal, JavierDuarte, BrenoOrzari....
Published date-11/30/2020

Abstract: We develop a graph generative adversarial network to generate sparse data sets like those produced at the CERN Large Hadron Collider (LHC). We demonstrate this approach by training on and …

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