Michael Poli

Orcid: 0000-0001-5384-9372

According to our database¹, Michael Poli authored at least 30 papers between 2019 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2024

STAR: Synthesis of Tailored Architectures.

[BibT_eX]

[DOI]

CoRR, 2024

Mechanistic Design and Scaling of Hybrid Architectures.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

State-Free Inference of State-Space Models: The *Transfer Function* Approach.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Zoology: Measuring and Improving Recall in Efficient Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Efficient Surrogate Dynamic Models with Graph Spline Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Latent State Space Models for Time-Series Generation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Hyena Hierarchy: Towards Larger Convolutional Language Models.

[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

Ideal Abstractions for Decision-Focused Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Optimal Energy Shaping via Neural Approximators.

[BibT_eX]

[DOI]

SIAM J. Appl. Dyn. Syst., September, 2022

Learning Stochastic Optimal Policies via Gradient Descent.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2022

Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations.

[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

Monarch: Expressive Structured Matrices for Efficient and Accurate Training.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Solvers for Fast and Accurate Numerical Optimal Control.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Continuous-Depth Neural Models for Dynamic Graph Prediction.

[BibT_eX]

[DOI]

CoRR, 2021

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions.

[BibT_eX]

[DOI]

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

Differentiable Multiple Shooting Layers.

[BibT_eX]

[DOI]

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

2020

Neural Ordinary Differential Equations for Intervention Modeling.

[BibT_eX]

[DOI]

CoRR, 2020

TorchDyn: A Neural Differential Equations Library.

[BibT_eX]

[DOI]

CoRR, 2020

Stable Neural Flows.

[BibT_eX]

[DOI]

CoRR, 2020

Hypersolvers: Toward Fast Continuous-Depth Models.

[BibT_eX]

[DOI]

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

Dissecting Neural ODEs.

[BibT_eX]

[DOI]

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

2019

Graph Neural Ordinary Differential Equations.

[BibT_eX]

[DOI]

CoRR, 2019

WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series.

[BibT_eX]

[DOI]

Michael Poli

Jinkyoo Park

Ilija Ilievski

CoRR, 2019

Port-Hamiltonian Approach to Neural Network Training.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Michael Poli

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