| Dissecting Neural ODEs S Massaroli, M Poli, P Jinkyoo, A Yamashita, H Asama Advances in Neural Information Processing Systems 34, 2020 | 75 | 2020 |
| Graph Neural Ordinary Differential Equations M Poli, S Massaroli, J Park, H Asama, A Yamashita, J Park arXiv preprint arXiv:1911.07532, 2019 | 31 | 2019 |
| Hypersolvers: Toward Fast Continuous-Depth Models M Poli, S Massaroli, A Yamashita, H Asama, J Park Advances in Neural Information Processing Systems 34, 2020 | 28 | 2020 |
| Stable Neural Flows S Massaroli, M Poli, M Bin, P Jinkyoo, A Yamashita, H Asama arXiv preprint arXiv:2003.08063, 2020 | 26 | 2020 |
| Torchdyn: A neural differential equations library M Poli, S Massaroli, A Yamashita, H Asama, J Park arXiv preprint arXiv:2009.09346, 2020 | 11 | 2020 |
| Port–Hamiltonian approach to neural network training S Massaroli, M Poli, F Califano, A Faragasso, J Park, A Yamashita, ... 2019 IEEE 58th Conference on Decision and Control (CDC), 6799-6806, 2019 | 10 | 2019 |
| Pedestrian trajectory prediction using BiRNN encoder–decoder framework J Wu, H Woo, Y Tamura, A Moro, S Massaroli, A Yamashita, H Asama Advanced Robotics 33 (18), 956-969, 2019 | 7 | 2019 |
| Differentiable Multiple Shooting Layers S Massaroli, M Poli, S Sonoda, T Suzuki, J Park, A Yamashita, H Asama Advances in Neural Information Processing Systems 34, 2021 | 6 | 2021 |
| Neural ordinary differential equations for intervention modeling D Gwak, G Sim, M Poli, S Massaroli, J Choo, E Choi arXiv preprint arXiv:2010.08304, 2020 | 3 | 2020 |
| Recursive algebraic frisch scheme: a particle-based approach S Massaroli, R Myagusuku, F Califano, C Melchiorri, A Yamashita, ... IFAC-PapersOnLine 51 (25), 409-415, 2018 | 3 | 2018 |
| Continuous-Depth Neural Models for Dynamic Graph Prediction M Poli, S Massaroli, CM Rabideau, J Park, A Yamashita, H Asama, J Park arXiv preprint arXiv:2106.11581, 2021 | 2 | 2021 |
| Optimal Energy Shaping via Neural Approximators S Massaroli, M Poli, F Califano, J Park, A Yamashita, H Asama arXiv preprint arXiv:2101.05537, 2021 | 2 | 2021 |
| Iterative Energy Shaping of a Ball–Dribbling Robot S Massaroli, F Califano, A Faragasso, A Yamashita, H Asama 1st IFAC Symposium on Robot Control (WROCO), 2019 | 2 | 2019 |
| A novel recursive linear estimator based on the frisch scheme S Massaroli, R Miyagusuku, F Califano, A Faragasso, A Yamashita, ... 2019 12th Asian Control Conference (ASCC), 1101-1106, 2019 | 2 | 2019 |
| Neural Solvers for Fast and Accurate Numerical Optimal Control F Berto, S Massaroli, M Poli, J Park arXiv preprint arXiv:2203.08072, 2022 | 1 | 2022 |
| Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions M Poli, S Massaroli, L Scimeca, S Chun, SJ Oh, A Yamashita, H Asama, ... Advances in Neural Information Processing Systems 34, 2021 | 1 | 2021 |
| Learning Stochastic Optimal Policies via Gradient Descent S Massaroli, M Poli, S Peluchetti, J Park, A Yamashita, H Asama IEEE Control Systems Letters 6, 1094-1099, 2021 | 1 | 2021 |
| On the extinction–free stabilization of predator-prey dynamics S Massaroli, F Califano, A Faragasso, A Yamashita, H Asama IEEE Control Systems Letters 4 (4), 964-969, 2020 | 1 | 2020 |
| Identification of a class of hybrid dynamical systems S Massaroli, F Califano, A Faragasso, M Risiglione, A Yamashita, ... IFAC-PapersOnLine 53 (2), 875-882, 2020 | 1 | 2020 |
| Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations M Poli, W Xu, S Massaroli, C Meng, K Kim, S Ermon arXiv preprint arXiv:2204.07673, 2022 | | 2022 |
Hajime AsamaUniversity of TokyoVerified email at robot.t.u-tokyo.ac.jp
