Search Results for author: Takanori Fujiwara

Found 15 papers, 5 papers with code

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

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

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 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

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.


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

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