Stefano Massaroli

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 44

Top Topics

Differential Equations

Transfer Function

Top Venues

IEEE Control. Syst. Lett.

Publications

Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Atsushi Yamashita, Michael Poli
State-Free Inference of State-Space Models: The Transfer Function Approach. CoRR (2024)
Michael Poli, Armin W. Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Ré, Ce Zhang, Stefano Massaroli
Mechanistic Design and Scaling of Hybrid Architectures. CoRR (2024)
Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio
What if We Enrich day-ahead Solar Irradiance Time Series Forecasting with Spatio-Temporal Context? CoRR (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. 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)
Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio
Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context. NeurIPS (2023)
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz
Ideal Abstractions for Decision-Focused Learning. AISTATS (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)
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)
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)
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)
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)
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)
Stefano Massaroli, Federico Califano, Angela Faragasso, Atsushi Yamashita, Hajime Asama
On the Extinction-Free Stabilization of Predator-Prey Dynamics. IEEE Control. Syst. Lett. 4 (4) (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)
Jiaxu Wu, Hanwool Woo, Yusuke Tamura, Alessandro Moro, Stefano Massaroli, Atsushi Yamashita, Hajime Asama
Pedestrian trajectory prediction using BiRNN encoder-decoder framework. Adv. Robotics 33 (18) (2019)
Stefano Massaroli, Renato Miyagusuku, Federico Califano, Angela Faragasso, Atsushi Yamashita, Hajime Asama
A Novel Recursive Linear Estimator Based on the Frisch Scheme. ASCC (2019)
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)
Stefano Massaroli, Michael Poli, Federico Califano, Angela Faragasso, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
Port-Hamiltonian Approach to Neural Network Training. CDC (2019)