Michael Poli

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 47

Top Topics

Differential Equations

Top Venues

Publications

Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré
Hyena Hierarchy: Towards Larger Convolutional Language Models. CoRR (2023)
Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR (2023)
Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré
Zoology: Measuring and Improving Recall in Efficient Language Models. CoRR (2023)
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
Ideal Abstractions for Decision-Focused Learning. AISTATS (2023)
Michael Zhang, Khaled Kamal Saab, Michael Poli, Tri Dao, Karan Goel, Christopher Ré
Effectively Modeling Time Series with Simple Discrete State Spaces. CoRR (2023)
Michael Zhang, Khaled Kamal Saab, Michael Poli, Tri Dao, Karan Goel, Christopher Ré
Effectively Modeling Time Series with Simple Discrete State Spaces. ICLR (2023)
Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Callum Birch-Sykes, Michael Wornow, Aman Patel, Clayton M. Rabideau, Stefano Massaroli, Yoshua Bengio, Stefano Ermon, Stephen A. Baccus, Christopher Ré
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. CoRR (2023)
Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. NeurIPS (2023)
Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks. CoRR (2023)
Daniel Y. Fu, Simran Arora, Jessica Grogan, Isys Johnson, Evan Sabri Eyuboglu, Armin W. Thomas, Benjamin Spector, Michael Poli, Atri Rudra, Christopher Ré
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture. NeurIPS (2023)
Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks. NeurIPS (2023)
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon
Deep Latent State Space Models for Time-Series Generation. ICML (2023)
Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré
Hyena Hierarchy: Towards Larger Convolutional Language Models. ICML (2023)
Daniel Y. Fu, Simran Arora, Jessica Grogan, Isys Johnson, Sabri Eyuboglu, Armin W. Thomas, Benjamin Spector, Michael Poli, Atri Rudra, Christopher Ré
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture. CoRR (2023)
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
Ideal Abstractions for Decision-Focused Learning. CoRR (2023)
Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS (2023)
Stefano Massaroli, Michael Poli, Federico Califano, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Optimal Energy Shaping via Neural Approximators. SIAM J. Appl. Dyn. Syst. 21 (3) (2022)
Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. CoRR (2022)
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, Stefano Ermon
Deep Latent State Space Models for Time-Series Generation. CoRR (2022)
Federico Berto, Stefano Massaroli, Michael Poli, Jinkyoo Park
Neural Solvers for Fast and Accurate Numerical Optimal Control. ICLR (2022)
Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Michael Poli, Sangdoo Yun
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective. ICLR (2022)
Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré
Monarch: Expressive Structured Matrices for Efficient and Accurate Training. ICML (2022)
Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon
Transform Once: Efficient Operator Learning in Frequency Domain. NeurIPS (2022)
Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. NeurIPS (2022)
Federico Berto, Stefano Massaroli, Michael Poli, Jinkyoo Park
Neural Solvers for Fast and Accurate Numerical Optimal Control. CoRR (2022)
Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon
Transform Once: Efficient Operator Learning in Frequency Domain. CoRR (2022)
Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré
Monarch: Expressive Structured Matrices for Efficient and Accurate Training. CoRR (2022)
Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Learning Stochastic Optimal Policies via Gradient Descent. IEEE Control. Syst. Lett. 6 (2022)
Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Michael Poli, Sangdoo Yun
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective. CoRR (2021)
Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg
Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. NeurIPS (2021)
Stefano Massaroli, Michael Poli, Stefano Peluchetti, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Learning Stochastic Optimal Policies via Gradient Descent. CoRR (2021)
Michael Poli, Stefano Massaroli, Clayton M. Rabideau, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
Continuous-Depth Neural Models for Dynamic Graph Prediction. CoRR (2021)
Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg
Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions. CoRR (2021)
Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Differentiable Multiple Shooting Layers. NeurIPS (2021)
Stefano Massaroli, Michael Poli, Federico Califano, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Optimal Energy Shaping via Neural Approximators. CoRR (2021)
Stefano Massaroli, Michael Poli, Sho Sonoda, Taji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Differentiable Multiple Shooting Layers. CoRR (2021)
Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
Hypersolvers: Toward Fast Continuous-Depth Models. NeurIPS (2020)
Stefano Massaroli, Michael Poli, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Dissecting Neural ODEs. NeurIPS (2020)
Stefano Massaroli, Michael Poli, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Dissecting Neural ODEs. CoRR (2020)
Stefano Massaroli, Michael Poli, Michelangelo Bin, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Stable Neural Flows. CoRR (2020)
Daehoon Gwak, Gyuhyeon Sim, Michael Poli, Stefano Massaroli, Jaegul Choo, Edward Choi
Neural Ordinary Differential Equations for Intervention Modeling. CoRR (2020)
Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
Hypersolvers: Toward Fast Continuous-Depth Models. CoRR (2020)
Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
TorchDyn: A Neural Differential Equations Library. CoRR (2020)
Michael Poli, Stefano Massaroli, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park
Graph Neural Ordinary Differential Equations. CoRR (2019)
Stefano Massaroli, Michael Poli, Federico Califano, Angela Faragasso, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Port-Hamiltonian Approach to Neural Network Training. CoRR (2019)
Michael Poli, Jinkyoo Park, Ilija Ilievski
WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series. CoRR (2019)
Stefano Massaroli, Michael Poli, Federico Califano, Angela Faragasso, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Port-Hamiltonian Approach to Neural Network Training. CDC (2019)