Dynamic Topological Data Analysis for Functional Brain Signals. - Tananun Songdechakraiwut; Moo K. Chung (ISBI Workshops, 2020)

Topological Learning for Brain Networks. - Tananun Songdechakraiwut; Moo K. Chung (CoRR, 2020)

Topological Learning and Its Application to Multimodal Brain Network Integration. - Tananun Songdechakraiwut; Li Shen 001; Moo K. Chung (MICCAI (2), 2021)

Fast topological clustering with Wasserstein distance. - Tananun Songdechakraiwut; Bryan M. Krause; Matthew I. Banks; Kirill V. Nourski; Barry D. Van Veen (ICLR, 2022)

Topological Classification in a Wasserstein Distance Based Vector Space. - Tananun Songdechakraiwut; Bryan M. Krause; Matthew I. Banks; Kirill V. Nourski; Barry D. Van Veen (CoRR, 2022)

Topological Continual Learning with Wasserstein Distance and Barycenter. - Tananun Songdechakraiwut; Xiaoshuang Yin; Barry D. Van Veen (CoRR, 2022)

Wasserstein Distance-Preserving Vector Space of Persistent Homology. - Tananun Songdechakraiwut; Bryan M. Krause; Matthew I. Banks; Kirill V. Nourski; Barry D. Van Veen (MICCAI (8), 2023)

Functional Connectomes of Neural Networks. - Tananun Songdechakraiwut; Yutong Wu (AAAI, 2025)