research
(*) is used to denote equal contribution. Author order determined via coin flips.
2021
- NeurIPS WS SpotlightNeural Solvers for Fast and Accurate Numerical Optimal ControlNeurIPS Workshop on the Symbiosis of Deep Learning and Differential Equations (DL-DE) 2021
- Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space PerspectiveTechnical Report 2021
- L-CSSLearning Stochastic Optimal Policies via Gradient DescentIEEE Control Systems Letters 2021
- NeurIPSNeural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic TransitionsAdvances in Neural Information Processing Systems, NeurIPS 2021
- NeurIPSDifferentiable Multiple Shooting LayersAdvances in Neural Information Processing Systems, NeurIPS 2021
- Optimal Energy Shaping via Neural ApproximatorsarXiv preprint arXiv:2101.05537 2021
2020
- NeurIPS Oral [1%]Dissecting Neural ODEsAdvances in Neural Information Processing Systems, NeurIPS 2020
- Neural Ordinary Differential Equations for Intervention ModelingarXiv preprint arXiv:2010.08304 2020
- NeurIPSHypersolvers: Toward Fast Continuous-Depth ModelsAdvances in Neural Information Processing Systems, NeurIPS 2020
- ICLR WSContinuous-Depth Value Networks For Parametrized ActionsICLR Workshop on Integration of Deep Neural Models and Differential Equations 2020
- ICLR WSPort-Hamiltonian Gradient FlowsICLR Workshop on Integration of Deep Neural Models and Differential Equations 2020
- IJCAIWATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time SeriesInternational Joint Conferences on Artificial Intelligence, IJCAI 2020
- Stable Neural FlowsTechnical Report 2020
- TorchDyn: Implicit Models and Neural Numerical Methods in PyTorchTechnical Report 2020
2019
- AAAI WSNeural Graph Differential EquationsInternational Workshop on Deep Learning on Graphs, DLGMA 2019
- CDCPort–Hamiltonian Approach to Neural Network TrainingIEEE Conference on Decision and Control, CDC 2019