Musical Creativity and Depth of Implicit Knowledge: Spectral and Temporal Individualities in Improvisation. - Tatsuya Daikoku (Frontiers Comput. Neurosci., 2018)

Entropy, Uncertainty, and the Depth of Implicit Knowledge on Musical Creativity: Computational Study of Improvisation in Melody and Rhythm. - Tatsuya Daikoku (Frontiers Comput. Neurosci., 2018)

Depth and the Uncertainty of Statistical Knowledge on Musical Creativity Fluctuate Over a Composer's Lifetime. - Tatsuya Daikoku (Frontiers Comput. Neurosci., 2019)

Tonality Tunes the Statistical Characteristics in Music: Computational Approaches on Statistical Learning. - Tatsuya Daikoku (Frontiers Comput. Neurosci., 2019)

Shaping the Epochal Individuality and Generality: The Temporal Dynamics of Uncertainty and Prediction Error in Musical Improvisation. - Tatsuya Daikoku (CoRR, 2023)

Quantitative Analysis of Training Methods, Data Size, and User-Specific Effectiveness in DL-Based Personalized Aesthetic Evaluation. - Yoshia Abe; Tatsuya Daikoku; Yasuo Kuniyoshi (PRICAI (1), 2024)

Assessing the Aesthetic Evaluation Capabilities of GPT-4 with Vision: Insights from Group and Individual Assessments. - Yoshia Abe; Tatsuya Daikoku; Yasuo Kuniyoshi (CoRR, 2024)

Emergence of integrated behaviors through direct optimization for homeostasis. - Naoto Yoshida; Tatsuya Daikoku; Yukie Nagai; Yasuo Kuniyoshi (Neural Networks, 2024)

Emotional Responses to Auditory Hierarchical Structures is Shaped by Bodily Sensations and Listeners' Sensory Traits. - Maiko Minatoya; Tatsuya Daikoku; Yasuo Kuniyoshi (CoRR, 2025)