no code implementations • 21 Sep 2024 • Xiaotong Zhang, Dingcheng Huang, Kamal Youcef-Toumi
In this paper, we further developed a novel two-loop framework integrating real-time and asynchronous processing to quantify relevance and apply relevance for safer and more efficient HRC.
no code implementations • 12 Sep 2024 • Xiaotong Zhang, DeAn Huang, Kamal Youcef-Toumi
Inspired by the human ability to selectively focus on relevant information, this paper introduces relevance, a novel dimensionality reduction process for human-robot collaboration (HRC).
no code implementations • 10 May 2024 • Tony Tohme, Mohammad Javad Khojasteh, Mohsen Sadr, Florian Meyer, Kamal Youcef-Toumi
The proposed ISR method naturally combines the principles of Invertible Neural Networks (INNs) and Equation Learner (EQL), a neural network-based symbolic architecture for function learning.
no code implementations • 30 Jan 2024 • Mohsen Sadr, Tony Tohme, Kamal Youcef-Toumi
Using variational calculus, we obtain an evolution equation for the Lagrange multipliers (adjoint equations) allowing us to compute the gradient of the objective function with respect to the parameters of PDEs given data in a straightforward manner.
no code implementations • 5 Oct 2023 • Aadi Kothari, Tony Tohme, Xiaotong Zhang, Kamal Youcef-Toumi
We propose a novel human motion prediction framework that incorporates human joint constraints and scene constraints in a Gaussian Process Regression (GPR) model to predict human motion over a set time horizon.
no code implementations • 7 Jun 2023 • Tony Tohme, Mohsen Sadr, Kamal Youcef-Toumi, Nicolas G. Hadjiconstantinou
We validate the proposed MESSY estimation method against other benchmark methods for the case of a bi-modal and a discontinuous density, as well as a density at the limit of physical realizability.
no code implementations • 31 May 2022 • Tony Tohme, Dehong Liu, Kamal Youcef-Toumi
Identifying the mathematical relationships that best describe a dataset remains a very challenging problem in machine learning, and is known as Symbolic Regression (SR).
no code implementations • 16 Sep 2021 • Tony Tohme, Kevin Vanslette, Kamal Youcef-Toumi
While deep neural networks are highly performant and successful in a wide range of real-world problems, estimating their predictive uncertainty remains a challenging task.
1 code implementation • 20 Aug 2021 • Alexandre Heuillet, Hedi Tabia, Hichem Arioui, Kamal Youcef-Toumi
This approach is accompanied by a novel metric that measures the distance between architectures inside our custom search space.
1 code implementation • 26 Oct 2020 • Quang H. Le, Kamal Youcef-Toumi, Dzmitry Tsetserukou, Ali Jahanian
Rethinking reconstruction networks as a generator, we define the problem of predicting masks as a GANs game framework: A segmentation network generates the masks, and a discriminator network decides on the quality of the masks.
no code implementations • 25 Sep 2019 • Mikio Furokawa, Erik Gest, Takayuki Hirano, Kamal Youcef-Toumi
However, it is difficult to perfectly control the collection timing of the measurements.