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How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections.

, , , , and . ICLR, OpenReview.net, (2023)

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How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections., , , , and . ICLR, OpenReview.net, (2023)Pretraining Without Attention., , , and . EMNLP (Findings), page 58-69. Association for Computational Linguistics, (2023)An Empirical Study of Mamba-based Language Models., , , , , , , , , and 6 other author(s). CoRR, (2024)Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models., , , , , , , , , and 7 other author(s). CoRR, (2024)Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling., , , , , and . ICML, OpenReview.net, (2024)Learning Compressed Transforms with Low Displacement Rank., , , , and . NeurIPS, page 9066-9078. (2018)HiPPO: Recurrent Memory with Optimal Polynomial Projections., , , , and . NeurIPS, (2020)Diagonal State Spaces are as Effective as Structured State Spaces., , and . NeurIPS, (2022)It's Raw! Audio Generation with State-Space Models., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 7616-7633. PMLR, (2022)The power of deferral: maintaining a constant-competitive steiner tree online., , and . STOC, page 525-534. ACM, (2013)