Cyrus Neary | DeepAI

AI Chat

Featured Co-authors

Ufuk Topcu
123 publications
Bo Chen
105 publications
Murat Cubuktepe
20 publications
Eric Goubault
19 publications
Matthew Hale
13 publications
Franck Djeumou
9 publications
Mustafa O. Karabag
6 publications
Sylvie Putot
6 publications
Christos Verginis
5 publications
Aryaman Singh Samyal
4 publications
Adam J. Thorpe
4 publications

∙ 09/09/2023

Verifiable Reinforcement Learning Systems via Compositionality

We propose a framework for verifiable and compositional reinforcement le...

0 Cyrus Neary, et al. ∙

∙ 08/10/2023

Multimodal Pretrained Models for Sequential Decision-Making: Synthesis, Verification, Grounding, and Perception

Recently developed pretrained models can encode rich world knowledge exp...

0 Yunhao Yang, et al. ∙

∙ 06/10/2023

How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations

We present a framework and algorithms to learn controlled dynamics model...

0 Franck Djeumou, et al. ∙

∙ 01/20/2023

Differential Privacy in Cooperative Multiagent Planning

Privacy-aware multiagent systems must protect agents' sensitive data whi...

0 Bo Chen, et al. ∙

∙ 01/09/2023

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control

Data-driven control algorithms use observations of system dynamics to co...

0 Adam J. Thorpe, et al. ∙

∙ 12/01/2022

Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks

Many dynamical systems – from robots interacting with their surroundings...

0 Cyrus Neary, et al. ∙

∙ 01/17/2022

Planning Not to Talk: Multiagent Systems that are Robust to Communication Loss

In a cooperative multiagent system, a collection of agents executes a jo...

0 Mustafa O. Karabag, et al. ∙

∙ 01/14/2022

Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs

Neural ordinary differential equations (NODEs) – parametrizations of dif...

0 Franck Djeumou, et al. ∙

∙ 09/14/2021

Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling

Effective inclusion of physics-based knowledge into deep neural network ...

0 Franck Djeumou, et al. ∙

∙ 06/07/2021

Verifiable and Compositional Reinforcement Learning Systems

We propose a novel framework for verifiable and compositional reinforcem...

0 Cyrus Neary, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world