Data Visualization
78 papers with code • 0 benchmarks • 2 datasets
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Latest papers
Curvature Augmented Manifold Embedding and Learning
A new dimensional reduction (DR) and data visualization method, Curvature-Augmented Manifold Embedding and Learning (CAMEL), is proposed.
From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models
This survey paper serves as a comprehensive resource for researchers and practitioners in the fields of natural language processing, computer vision, and data analysis, providing valuable insights and directions for future research in chart understanding leveraging large foundation models.
DiffRed: Dimensionality Reduction guided by stable rank
We rigorously prove that DiffRed achieves a general upper bound of $O\left(\sqrt{\frac{1-p}{k_2}}\right)$ on Stress and $O\left(\frac{(1-p)}{\sqrt{k_2*\rho(A^{*})}}\right)$ on M1 where $p$ is the fraction of variance explained by the first $k_1$ principal components and $\rho(A^{*})$ is the stable rank of $A^{*}$.
MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization
Scientific data visualization plays a crucial role in research by enabling the direct display of complex information and assisting researchers in identifying implicit patterns.
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion Detection
The results show nearly perfect classification performance when the models are trained and tested on the same dataset.
ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning
Charts play a vital role in data visualization, understanding data patterns, and informed decision-making.
LLM4Vis: Explainable Visualization Recommendation using ChatGPT
To obtain demonstration examples with high-quality explanations, we propose a new explanation generation bootstrapping to iteratively refine generated explanations by considering the previous generation and template-based hint.
Supervised Stochastic Neighbor Embedding Using Contrastive Learning
Stochastic neighbor embedding (SNE) methods $t$-SNE, UMAP are two most popular dimensionality reduction methods for data visualization.
Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization
We address this shortcoming with an adaptively placed multi-grid SRN (APMGSRN) and propose a domain decomposition training and inference technique for accelerated parallel training on multi-GPU systems.
Surgical Phase and Instrument Recognition: How to identify appropriate Dataset Splits
It focuses on the visualization of the occurrence of phases, phase transitions, instruments, and instrument combinations across sets.