Search Results for author: Kwan-Liu Ma

Found 38 papers, 10 papers with code

A Visual Analytics Design for Connecting Healthcare Team Communication to Patient Outcomes

no code implementations8 Jan 2024 Hsiao-Ying Lu, Yiran Li, Kwan-Liu Ma

Communication among healthcare professionals (HCPs) is crucial for the quality of patient treatment.

Visual Analytics for Efficient Image Exploration and User-Guided Image Captioning

no code implementations2 Nov 2023 Yiran Li, Junpeng Wang, Prince Aboagye, Michael Yeh, Yan Zheng, Liang Wang, Wei zhang, Kwan-Liu Ma

On the one hand, by visually examining the captions automatically generated from language-image models for an image dataset, we gain deeper insights into the semantic underpinnings of the visual contents, unearthing data biases that may be entrenched within the dataset.

Efficient Exploration Image Captioning

Classes are not Clusters: Improving Label-based Evaluation of Dimensionality Reduction

1 code implementation1 Aug 2023 Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit, Kwan-Liu Ma, Jinwook Seo

In this paper, we introduce two novel quality measures -- Label-Trustworthiness and Label-Continuity (Label-T&C) -- advancing the process of DR evaluation based on class labels.

Dimensionality Reduction

A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems

no code implementations15 Jun 2023 Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

This end-to-end log analysis system, coupled with visual analytics support, allows users to glean and promptly extract supercomputer usage and error patterns at varying temporal and spatial resolutions.

Photon Field Networks for Dynamic Real-Time Volumetric Global Illumination

no code implementations14 Apr 2023 David Bauer, Qi Wu, Kwan-Liu Ma

In this paper, we present a novel method to enable real-time global illumination for volume data visualization.

Data Visualization

HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillation

no code implementations9 Apr 2023 Qi Wu, David Bauer, Yuyang Chen, Kwan-Liu Ma

Implicit Neural Representations (INRs) have recently exhibited immense potential in the field of scientific visualization for both data generation and visualization tasks.

Knowledge Distillation Novel View Synthesis +1

Distributed Neural Representation for Reactive in situ Visualization

no code implementations28 Mar 2023 Qi Wu, Joseph A. Insley, Victor A. Mateevitsi, Silvio Rizzi, Michael E. Papka, Kwan-Liu Ma

In this work, we develop an implicit neural representation for distributed volume data and incorporate it into the DIVA reactive programming system.

How Does Attention Work in Vision Transformers? A Visual Analytics Attempt

no code implementations24 Mar 2023 Yiran Li, Junpeng Wang, Xin Dai, Liang Wang, Chin-Chia Michael Yeh, Yan Zheng, Wei zhang, Kwan-Liu Ma

Multi-head self-attentions are then applied to the sequence to learn the attention between patches.

Visual Analytics of Neuron Vulnerability to Adversarial Attacks on Convolutional Neural Networks

no code implementations6 Mar 2023 Yiran Li, Junpeng Wang, Takanori Fujiwara, Kwan-Liu Ma

Adversarial attacks on a convolutional neural network (CNN) -- injecting human-imperceptible perturbations into an input image -- could fool a high-performance CNN into making incorrect predictions.

Autonomous Driving Medical Diagnosis +1

SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective

no code implementations1 Mar 2023 Xiwei Xuan, Ziquan Deng, Hsuan-Tien Lin, Zhaodan Kong, Kwan-Liu Ma

Researchers have proposed various methods for visually interpreting the Convolutional Neural Network (CNN) via saliency maps, which include Class-Activation-Map (CAM) based approaches as a leading family.

FoVolNet: Fast Volume Rendering using Foveated Deep Neural Networks

no code implementations20 Sep 2022 David Bauer, Qi Wu, Kwan-Liu Ma

We introduce FoVolNet -- a method to significantly increase the performance of volume data visualization.

Data Visualization Image Reconstruction +1

Interactive Volume Visualization via Multi-Resolution Hash Encoding based Neural Representation

1 code implementation23 Jul 2022 Qi Wu, David Bauer, Michael J. Doyle, Kwan-Liu Ma

Neural networks have shown great potential in compressing volume data for visualization.

VAC-CNN: A Visual Analytics System for Comparative Studies of Deep Convolutional Neural Networks

no code implementations25 Oct 2021 Xiwei Xuan, XiaoYu Zhang, Oh-Hyun Kwon, Kwan-Liu Ma

The rapid development of Convolutional Neural Networks (CNNs) in recent years has triggered significant breakthroughs in many machine learning (ML) applications.

Image Classification

A Deep Generative Model for Reordering Adjacency Matrices

no code implementations11 Oct 2021 Oh-Hyun Kwon, Chiun-How Kao, Chun-houh Chen, Kwan-Liu Ma

Depending on the node ordering, an adjacency matrix can highlight distinct characteristics of a graph.

Interactive Dimensionality Reduction for Comparative Analysis

1 code implementation29 Jun 2021 Takanori Fujiwara, Xinhai Wei, Jian Zhao, Kwan-Liu Ma

However, existing DR methods provide limited capability and flexibility for such comparative analysis as each method is designed only for a narrow analysis target, such as identifying factors that most differentiate groups.

Contrastive Learning Dimensionality Reduction

HypperSteer: Hypothetical Steering and Data Perturbation in Sequence Prediction with Deep Learning

no code implementations4 Nov 2020 Chuan Wang, Kwan-Liu Ma

Deep Recurrent Neural Networks (RNN) continues to find success in predictive decision-making with temporal event sequences.

Decision Making

A Predictive Visual Analytics System for Studying Neurodegenerative Disease based on DTI Fiber Tracts

no code implementations13 Oct 2020 Chaoqing Xu, Tyson Neuroth, Takanori Fujiwara, Ronghua Liang, Kwan-Liu Ma

Diffusion tensor imaging (DTI) has been used to study the effects of neurodegenerative diseases on neural pathways, which may lead to more reliable and early diagnosis of these diseases as well as a better understanding of how they affect the brain.

A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems' Worldviews

no code implementations3 Sep 2020 Suyun Bae, Federico Rossi, Joshua Vander Hook, Scott Davidoff, Kwan-Liu Ma

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot's abilities, hold great promise for a number of applications, such as planetary exploration missions.

Human-Computer Interaction Multiagent Systems Robotics

P6: A Declarative Language for Integrating Machine Learning in Visual Analytics

1 code implementation3 Sep 2020 Jianping Kelvin Li, Kwan-Liu Ma

We present P6, a declarative language for building high performance visual analytics systems through its support for specifying and integrating machine learning and interactive visualization methods.

BIG-bench Machine Learning

A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction

no code implementations2 Aug 2020 Takanori Fujiwara, Shilpika, Naohisa Sakamoto, Jorji Nonaka, Keiji Yamamoto, Kwan-Liu Ma

Data-driven problem solving in many real-world applications involves analysis of time-dependent multivariate data, for which dimensionality reduction (DR) methods are often used to uncover the intrinsic structure and features of the data.

Contrastive Learning Dimensionality Reduction +2

A Visual Analytics Framework for Contrastive Network Analysis

no code implementations1 Aug 2020 Takanori Fujiwara, Jian Zhao, Francine Chen, Kwan-Liu Ma

A common network analysis task is comparison of two networks to identify unique characteristics in one network with respect to the other.

BIG-bench Machine Learning Contrastive Learning +1

Scalable Comparative Visualization of Ensembles of Call Graphs

1 code implementation1 Jul 2020 Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma

Optimizing the performance of large-scale parallel codes is critical for efficient utilization of computing resources.

Distributed, Parallel, and Cluster Computing Performance

Network Comparison with Interpretable Contrastive Network Representation Learning

3 code implementations25 May 2020 Takanori Fujiwara, Jian Zhao, Francine Chen, Yao-Liang Yu, Kwan-Liu Ma

This analysis task could be greatly assisted by contrastive learning, which is an emerging analysis approach to discover salient patterns in one dataset relative to another.

Contrastive Learning Representation Learning

Comparative Visual Analytics for Assessing Medical Records with Sequence Embedding

no code implementations18 Feb 2020 Rongchen Guo, Takanori Fujiwara, Yiran Li, Kelly M. Lima, Soman Sen, Nam K. Tran, Kwan-Liu Ma

While we use an autoencoder for the event embedding, we apply its variant with the self-attention mechanism for the sequence embedding.

A Visual Analytics System for Multi-model Comparison on Clinical Data Predictions

no code implementations18 Feb 2020 Yiran Li, Takanori Fujiwara, Yong K. Choi, Katherine K. Kim, Kwan-Liu Ma

Through a case study of a publicly available clinical dataset, we demonstrate the effectiveness of our visual analytics system to assist clinicians and researchers in comparing and quantitatively evaluating different machine learning methods.

BIG-bench Machine Learning Decision Making

A Visual Analytics Framework for Reviewing Streaming Performance Data

1 code implementation26 Jan 2020 Suraj P. Kesavan, Takanori Fujiwara, Jianping Kelvin Li, Caitlin Ross, Misbah Mubarak, Christopher D. Carothers, Robert B. Ross, Kwan-Liu Ma

To support streaming data analysis, we introduce a visual analytic framework comprising of three modules: data management, analysis, and interactive visualization.

Management

An Incremental Dimensionality Reduction Method for Visualizing Streaming Multidimensional Data

no code implementations10 May 2019 Takanori Fujiwara, Jia-Kai Chou, Shilpika, Panpan Xu, Liu Ren, Kwan-Liu Ma

We enhance an existing incremental PCA method in several ways to ensure its usability for visualizing streaming multidimensional data.

Dimensionality Reduction

Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning

no code implementations10 May 2019 Takanori Fujiwara, Oh-Hyun Kwon, Kwan-Liu Ma

Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-dimensional data as it provides a good first glance of the data.

Clustering Contrastive Learning +1

A Deep Generative Model for Graph Layout

1 code implementation27 Apr 2019 Oh-Hyun Kwon, Kwan-Liu Ma

To provide users with an intuitive way to navigate the layout design space, we present a technique to systematically visualize a graph in diverse layouts using deep generative models.

3D Depth Estimation Layout Design +1

Multifaceted 4D Feature Segmentation and Extraction in Point and Field-based Datasets

no code implementations28 Mar 2019 Franz Sauer, Kwan-Liu Ma

In this work, we present a new 4D feature segmentation/extraction scheme that can operate on both the field and point/trajectory data types simultaneously.

What Would a Graph Look Like in This Layout? A Machine Learning Approach to Large Graph Visualization

no code implementations11 Oct 2017 Oh-Hyun Kwon, Tarik Crnovrsanin, Kwan-Liu Ma

For a given graph, our approach can show what the graph would look like in different layouts and estimate their corresponding aesthetic metrics.

Learning to Compose with Professional Photographs on the Web

1 code implementation1 Feb 2017 Yi-Ling Chen, Jan Klopp, Min Sun, Shao-Yi Chien, Kwan-Liu Ma

Photo composition is an important factor affecting the aesthetics in photography.

Image Cropping

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