Search Results - "Songdechakraiwut, Tananun"

Scalable Topological Framework for Machine Learning by Songdechakraiwut, Tananun

“…The study of brain networks has long been recognized as a crucial avenue for understanding various neurological disorders, including epilepsy, autism, and…”
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Dynamic Topological Data Analysis for Functional Brain Signals by Songdechakraiwut, Tananun, Chung, Moo K.

“…We propose a novel dynamic topological data analysis (TDA) framework that builds persistent homology over a time series of 3D functional brain images. The…”
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Topological Learning for Brain Networks by Songdechakraiwut, Tananun, Chung, Moo K

“…Ann. Appl. Stat. 17(1): 403-433 (March 2023) This paper proposes a novel topological learning framework that integrates networks of different sizes and…”
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Topological Continual Learning with Wasserstein Distance and Barycenter by Songdechakraiwut, Tananun, Yin, Xiaoshuang, Van Veen, Barry D

“…Continual learning in neural networks suffers from a phenomenon called catastrophic forgetting, in which a network quickly forgets what was learned in a…”
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Topological Classification in a Wasserstein Distance Based Vector Space by Songdechakraiwut, Tananun, Krause, Bryan M, Banks, Matthew I, Nourski, Kirill V, Van Veen, Barry D

“…Classification of large and dense networks based on topology is very difficult due to the computational challenges of extracting meaningful topological…”
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Fast Topological Clustering with Wasserstein Distance by Songdechakraiwut, Tananun, Krause, Bryan M, Banks, Matthew I, Nourski, Kirill V, Van Veen, Barry D

“…The topological patterns exhibited by many real-world networks motivate the development of topology-based methods for assessing the similarity of networks…”
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Statistical Analysis of Dynamic Functional Brain Networks in Twins by Chung, Moo K, Huang, Shih-Gu, Songdechakraiwut, Tananun, Carroll, Ian C, Goldsmith, H. Hill

“…Recent studies have shown that functional brain brainwork is dynamic even during rest. A common approach to modeling the brain network in whole brain…”
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