Papers Data Visualization
“Data Visualization” 태그가 달린 논문 335편 · 필터 해제
Lumos in the Night Sky: AI-enabled Visual Tool for Exploring Night-Time Light Patterns
We introduce NightPulse, an interactive tool for Night-time light (NTL) data visualization and analytics, which enables researchers and stakeholders to explore and analyze NTL data with a user-friendly platform. Powered …
ClusteringData VisualizationImage SegmentationSemantic SegmentationChatGPT as your Personal Data Scientist
The rise of big data has amplified the need for efficient, user-friendly automated machine learning (AutoML) tools. However, the intricacy of understanding domain-specific data and defining prediction tasks necessitates …
AutoMLData VisualizationCollection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets
We introduce the Collection Space Navigator (CSN), a browser-based visualization tool to explore, research, and curate large collections of visual digital artifacts that are associated with multidimensional data, such as…
Data VisualizationDimensionality ReductionEmbeddings EvaluationContext-Aware Chart Element Detection
As a prerequisite of chart data extraction, the accurate detection of chart basic elements is essential and mandatory. In contrast to object detection in the general image domain, chart element detection relies heavily o…
Data VisualizationDocument AIobject-detectionObject DetectionLineFormer: Rethinking Line Chart Data Extraction as Instance Segmentation
Data extraction from line-chart images is an essential component of the automated document understanding process, as line charts are a ubiquitous data visualization format. However, the amount of visual and structural va…
Data Visualizationdocument understandingInstance SegmentationSemantic SegmentationEllipsoid fitting with the Cayley transform
We introduce Cayley transform ellipsoid fitting (CTEF), an algorithm that uses the Cayley transform to fit ellipsoids to noisy data in any dimension. Unlike many ellipsoid fitting methods, CTEF is ellipsoid specific, mea…
ClusteringData VisualizationDimensionality ReductionRhythmPhoton Field Networks for Dynamic Real-Time Volumetric Global Illumination
Volume data is commonly found in many scientific disciplines, like medicine, physics, and biology. Experts rely on robust scientific visualization techniques to extract valuable insights from the data. Recent years have …
Data VisualizationReDWINE: A Clinical Datamart with Text Analytical Capabilities to Facilitate Rehabilitation Research
Rehabilitation research focuses on determining the components of a treatment intervention, the mechanism of how these components lead to recovery and rehabilitation, and ultimately the optimal intervention strategies to …
Data VisualizationNeuroDAVIS: A neural network model for data visualization
The task of dimensionality reduction and visualization of high-dimensional datasets remains a challenging problem since long. Modern high-throughput technologies produce newer high-dimensional datasets having multiple vi…
Data VisualizationDimensionality ReductionmodelMulti-task Meta Label Correction for Time Series Prediction
Time series classification faces two unavoidable problems. One is partial feature information and the other is poor label quality, which may affect model performance. To address the above issues, we create a label correc…
Contrastive LearningData VisualizationMeta-LearningMulti-Task Learning+4Ask and You Shall Receive (a Graph Drawing): Testing ChatGPT's Potential to Apply Graph Layout Algorithms
Large language models (LLMs) have recently taken the world by storm. They can generate coherent text, hold meaningful conversations, and be taught concepts and basic sets of instructions - such as the steps of an algorit…
Data VisualizationReinforced Labels: Multi-Agent Deep Reinforcement Learning for Point-Feature Label Placement
Over the recent years, Reinforcement Learning combined with Deep Learning techniques has successfully proven to solve complex problems in various domains, including robotics, self-driving cars, and finance. In this paper…
Data VisualizationDeep Reinforcement Learningreinforcement-learningReinforcement Learning+2Linear-scaling kernels for protein sequences and small molecules outperform deep learning while providing uncertainty quantitation and improved interpretability
Gaussian process (GP) is a Bayesian model which provides several advantages for regression tasks in machine learning such as reliable quantitation of uncertainty and improved interpretability. Their adoption has been pre…
Data VisualizationDrug DiscoveryFormation EnergyProtein Function PredictionImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound
Most packages for the analysis of fMRI-based functional connectivity (FC) and genomic data are used with a programming language interface, lacking an easy-to-navigate GUI frontend. This exacerbates two problems found in …
Data VisualizationFunctional ConnectivityNavigateXNLI: Explaining and Diagnosing NLI-based Visual Data Analysis
Natural language interfaces (NLIs) enable users to flexibly specify analytical intentions in data visualization. However, diagnosing the visualization results without understanding the underlying generation process is ch…
Data VisualizationDeep Generative Neural Embeddings for High Dimensional Data Visualization
We propose a visualization technique that utilizes neural network embeddings and a generative network to reconstruct original data. This method allows for independent manipulation of individual image embeddings through i…
Data VisualizationVocal Bursts Intensity PredictionA general framework for implementing distances for categorical variables
The degree to which subjects differ from each other with respect to certain properties measured by a set of variables, plays an important role in many statistical methods. For example, classification, clustering, and dat…
Data VisualizationDeep Clustering of Tabular Data by Weighted Gaussian Distribution Learning
Deep learning methods are primarily proposed for supervised learning of images or text with limited applications to clustering problems. In contrast, tabular data with heterogeneous features pose unique challenges in rep…
ClusteringData VisualizationDeep ClusteringDeep Learning+1Two-sample test based on Self-Organizing Maps
Machine-learning classifiers can be leveraged as a two-sample statistical test. Suppose each sample is assigned a different label and that a classifier can obtain a better-than-chance result discriminating them. In this …
Data VisualizationDimensionality ReductionVocal Bursts Valence PredictionCompacter networks as a defensive mechanism: How firms clustered during 2015 Financial Crisis in China
The stock market's reaction to the external risk shock is closely related to the cross-shareholding network structure. This paper takes the public information of listed companies in the A-share securities market as the p…
ClusteringData Visualization