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Deep Learning the EEG Manifold for Phonological Categorization from Active Thoughts.

, , and . ICASSP, page 2762-2766. IEEE, (2019)

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Hierarchical Deep Feature Learning for Decoding Imagined Speech from EEG., and . AAAI, page 10019-10020. AAAI Press, (2019)Deep Learning the EEG Manifold for Phonological Categorization from Active Thoughts., , and . ICASSP, page 2762-2766. IEEE, (2019)Learning Joint Articulatory-Acoustic Representations with Normalizing Flows., and . INTERSPEECH, page 3196-3200. ISCA, (2020)Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI., , and . INTERSPEECH, page 1249-1253. ISCA, (2018)Rethinking Semi-Supervised Federated Learning: How to Co-train Fully-Labeled and Fully-Unlabeled Client Imaging Data., , and . MICCAI (2), volume 14221 of Lecture Notes in Computer Science, page 414-424. Springer, (2023)A fast local gradient based super-resolution image reconstruction algorithm with fuzzy hyper-bias learning and sparse monitoring paradigm., , and . ReTIS, page 399-404. IEEE, (2015)Sound-Stream II: Towards Real-Time Gesture Controlled Articulatory Sound Synthesis., , , and . CoRR, (2018)The Promise of Analog Deep Learning: Recent Advances, Challenges and Opportunities., and . CoRR, (2024)Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities., , , , , , , , and . CoRR, (2024)Dual Conditioned Diffusion Models for Out-of-Distribution Detection: Application to Fetal Ultrasound Videos., , , , and . MICCAI (1), volume 14220 of Lecture Notes in Computer Science, page 216-226. Springer, (2023)