Representation tradeoffs for hyperbolic embeddings C De Sa, A Gu, C Ré, F Sala Proceedings of machine learning research 80, 4460, 2018 | 98 | 2018 |

The power of deferral: maintaining a constant-competitive steiner tree online A Gu, A Gupta, A Kumar SIAM Journal on Computing 45 (1), 1-28, 2016 | 38 | 2016 |

Learning mixed-curvature representations in product spaces A Gu, F Sala, B Gunel, C Ré International Conference on Learning Representations, 2018 | 32 | 2018 |

A kernel theory of modern data augmentation T Dao, A Gu, AJ Ratner, V Smith, C De Sa, C Ré Proceedings of machine learning research 97, 1528, 2019 | 24 | 2019 |

Learning compressed transforms with low displacement rank A Thomas, A Gu, T Dao, A Rudra, C Ré Advances in neural information processing systems, 9052-9060, 2018 | 12 | 2018 |

Learning fast algorithms for linear transforms using butterfly factorizations T Dao, A Gu, M Eichhorn, A Rudra, C Ré Proceedings of machine learning research 97, 1517, 2019 | 9 | 2019 |

Christopher Ré. A kernel theory of modern data augmentation T Dao, A Gu, AJ Ratner, V Smith, C De Sa arXiv preprint arXiv:1803.06084, 2018 | 5 | 2018 |

A two-pronged progress in structured dense matrix vector multiplication C De Sa, A Cu, R Puttagunta, C Ré, A Rudra Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 5 | 2018 |

Recurrence width for structured dense matrix vector multiplication A Gu, R Puttagunta, C Ré, A Rudra arXiv preprint arXiv:1611.01569, 2016 | 2 | 2016 |

HiPPO: Recurrent Memory with Optimal Polynomial Projections A Gu, T Dao, S Ermon, A Rudra, C Re arXiv preprint arXiv:2008.07669, 2020 | 1 | 2020 |

Sparse Recovery for Orthogonal Polynomial Transforms A Gilbert, A Gu, C Re, A Rudra, M Wootters arXiv preprint arXiv:1907.08362, 2019 | 1 | 2019 |

Learning invariance with compact transforms AT Thomas, A Gu, T Dao, A Rudra, C Ré | 1 | 2018 |

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation K Goel, A Gu, Y Li, C Ré arXiv preprint arXiv:2008.06775, 2020 | | 2020 |

Improving the Gating Mechanism of Recurrent Neural Networks A Gu, C Gulcehre, TL Paine, M Hoffman, R Pascanu arXiv preprint arXiv:1910.09890, 2019 | | 2019 |

Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps T Dao, N Sohoni, A Gu, M Eichhorn, A Blonder, M Leszczynski, A Rudra, ... International Conference on Learning Representations, 2019 | | 2019 |

Sprague-Grundy Values of the -Wythoff Game A Gu The Electronic Journal of Combinatorics 22 (2), P2. 13, 2015 | | 2015 |