https://speakerdeck.com/pedrodevog 2026-06-15 08:15:04 -0400 In this Biomed Seminar, Pedro Devogelaere (KU Leuven) presents "Efficient long-sequence learning with deep State Space Models." The talk covers the theoretical foundations of High-order Polynomial Projection Operations (HiPPO) and Structured State Spaces (S4), and how these methods enable efficient modeling of long sequences. A biomedical application in automated sleep staging is then explored, comparing the S4-based S4Sleep model against the RNN-based L-SeqSleepNet on standard polysomnography benchmarks. In this Biomed Seminar, Pedro Devogelaere (KU Leuven) presents "Efficient long-sequence learning with deep State Space Models." The talk covers the theoretical foundations of High-order Polynomial Projection Operations (HiPPO) and Structured State Spaces (S4), and how these methods enable efficient modeling of long sequences. A biomedical application in automated sleep staging is then explored, comparing the S4-based S4Sleep model against the RNN-based L-SeqSleepNet on standard polysomnography benchmarks. Mon, 15 Jun 2026 00:00:00 -0400 https://speakerdeck.com/pedrodevog/efficient-long-sequence-learning-with-deep-state-space-models https://speakerdeck.com/pedrodevog/efficient-long-sequence-learning-with-deep-state-space-models