Tri Dao

According to our database¹, Tri Dao authored at least 40 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling.

[BibT_eX]

[DOI]

CoRR, 2024

StarCoder 2 and The Stack v2: The Next Generation.

[BibT_eX]

[DOI]

CoRR, 2024

BitDelta: Your Fine-Tune May Only Be Worth One Bit.

[BibT_eX]

[DOI]

CoRR, 2024

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

[BibT_eX]

[DOI]

Albert Gu

Tri Dao

CoRR, 2023

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

[BibT_eX]

[DOI]

Tri Dao

CoRR, 2023

StarCoder: may the source be with you!

[BibT_eX]

[DOI]

Evgenii Zheltonozhskii

Logesh Kumar Umapathi

Urvashi Bhattacharyya

Carolyn Jane Anderson

Carlos Muñoz Ferrandis

CoRR, 2023

Hyena Hierarchy: Towards Larger Convolutional Language Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time.

[BibT_eX]

[DOI]

Anshumali Shrivastava

Proceedings of the International Conference on Machine Learning, 2023

Simple Hardware-Efficient Long Convolutions for Sequence Modeling.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Effectively Modeling Time Series with Simple Discrete State Spaces.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hungry Hungry Hippos: Towards Language Modeling with State Space Models.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces.

[BibT_eX]

[DOI]

CoRR, 2022

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees.

[BibT_eX]

[DOI]

CoRR, 2022

Decentralized Training of Foundation Models in Heterogeneous Environments.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transform Once: Efficient Operator Learning in Frequency Domain.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ButterflyFlow: Building Invertible Layers with Butterfly Matrices.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Monarch: Expressive Structured Matrices for Efficient and Accurate Training.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Scatterbrain: Unifying Sparse and Low-rank Attention Approximation.

[BibT_eX]

[DOI]

CoRR, 2021

Rethinking Neural Operations for Diverse Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scatterbrain: Unifying Sparse and Low-rank Attention.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Catformer: Designing Stable Transformers via Sensitivity Analysis.

[BibT_eX]

[DOI]

Jared Quincy Davis

Albert Gu

Krzysztof Choromanski

Proceedings of the 38th International Conference on Machine Learning, 2021

Knowledge Distillation as Semiparametric Inference.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training.

[BibT_eX]

[DOI]

Anshumali Shrivastava

Christopher Ré

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

HiPPO: Recurrent Memory with Optimal Polynomial Projections.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Adaptive Hashing for Model Counting.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On the Downstream Performance of Compressed Word Embeddings.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Approximating the Permanent by Sampling from Adaptive Partitions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Kernel Theory of Modern Data Augmentation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning Compressed Transforms with Low Displacement Rank.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Invariance with Compact Transforms.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Gaussian Quadrature for Kernel Features.

[BibT_eX]

[DOI]

Tri Dao

Christopher De Sa

Christopher Ré

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Tri Dao

Timeline

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On csauthors.net:

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