Search Results for author: Kwan-Liu Ma

Found 22 papers, 7 papers with code

CNNC: 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

With a carefully designed model visualization and explaining support, CNNC facilitates a highly interactive workflow that promptly presents both quantitative and qualitative information at each analysis stage.

Image Classification

A Deep Generative Model for Matrix Reordering

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.

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.

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

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 +1

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.

Contrastive Learning Representation Learning

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

Interpretable Contrastive Learning for Networks

1 code implementation25 May 2020 Takanori Fujiwara, Jian Zhao, Francine Chen, Yao-Liang Yu, Kwan-Liu Ma

Contrastive learning (CL) is an emerging analysis approach that aims to discover unique 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.

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.

Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks

no code implementations23 Jan 2020 Chuan Wang, Xumeng Wang, Kwan-Liu Ma

Deep Recurrent Neural Networks (RNN) is increasingly used in decision-making with temporal sequences.

Decision Making

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.

Contrastive Learning Dimensionality Reduction

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

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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