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pro vyhledávání: '"Telea, A."'
Is it true that if citizens understand hurricane probabilities, they will make more rational decisions for evacuation? Finding answers to such questions is not straightforward in the literature because the terms judgment and decision making are often
Externí odkaz:
http://arxiv.org/abs/2312.12921
Projections, or dimensionality reduction methods, are techniques of choice for the visual exploration of high-dimensional data. Many such techniques exist, each one of them having a distinct visual signature - i.e., a recognizable way to arrange poin
Externí odkaz:
http://arxiv.org/abs/2306.00554
Planar drawings of graphs tend to be favored over non-planar drawings. Testing planarity and creating a planar layout of a planar graph can be done in linear time. However, creating readable drawings of nearly planar graphs remains a challenge. We th
Externí odkaz:
http://arxiv.org/abs/2304.07274
As the complexity of machine learning (ML) models increases and their application in different (and critical) domains grows, there is a strong demand for more interpretable and trustworthy ML. A direct, model-agnostic, way to interpret such models is
Externí odkaz:
http://arxiv.org/abs/2304.00133
Lacking supervised data is an issue while training deep neural networks (DNNs), mainly when considering medical and biological data where supervision is expensive. Recently, Embedded Pseudo-Labeling (EPL) addressed this problem by using a non-linear
Externí odkaz:
http://arxiv.org/abs/2302.02663
Publikováno v:
In Computers & Graphics November 2024 124
Publikováno v:
In Computers & Graphics November 2024 124
Autor:
Espadoto, Mateus, Appleby, Gabriel, Suh, Ashley, Cashman, Dylan, Li, Mingwei, Scheidegger, Carlos, Anderson, Erik W, Chang, Remco, Telea, Alexandru C
Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen. Although many such methods exist, comparably little work has been done on g
Externí odkaz:
http://arxiv.org/abs/2111.01744
Applying dimensionality reduction (DR) to large, high-dimensional data sets can be challenging when distinguishing the underlying high-dimensional data clusters in a 2D projection for exploratory analysis. We address this problem by first sharpening
Externí odkaz:
http://arxiv.org/abs/2110.00317
Publikováno v:
In Computers & Graphics August 2024 122