Proceedings of the National Academy of Sciences of the United States of America
Oct 26, 2021
In this paper, we introduce the , a nonconvex, yet analytically tractable, optimization program, in a quest to better understand deep neural networks that are trained for a sufficiently long time. As the name suggests, this model is derived by isolat...
Chaos (Woodbury, N.Y.)
Oct 1, 2021
We focus on chaotic dynamical systems and analyze their time series with the use of autoencoders, i.e., configurations of neural networks that map identical output to input. This analysis results in the determination of the latent space dimension of ...
The Review of scientific instruments
Sep 1, 2021
Series elastic actuators (SEAs) have widely been adapted in robots where safe human-robot interaction is required for accurate and robust force control. Recent research on the SEAs has shown that the SEA with a user-defined variable stiffness possess...
Chaos (Woodbury, N.Y.)
Jan 1, 2021
We propose an extended reservoir computer that shows the functional differentiation of neurons. The reservoir computer is developed to enable changing of the internal reservoir using evolutionary dynamics, and we call it an evolutionary reservoir com...
Chaos (Woodbury, N.Y.)
Jan 1, 2021
A state observer plays a vital role in the design of state feedback neuromodulation schemes used to prevent and treat neurological or psychiatric disorders. This paper aims to design a state observer to reconstruct all unmeasured states of the comput...
Anesthesia and analgesia
Nov 1, 2020
BACKGROUND: Induction of anesthesia is a phase characterized by rapid changes in both drug concentration and drug effect. Conventional mammillary compartmental models are limited in their ability to accurately describe the early drug distribution kin...
Physical review letters
Oct 23, 2020
Deep learning has achieved impressive prediction accuracies in a variety of scientific and industrial domains. However, the nested nonlinear feature of deep learning makes the learning highly nontransparent, i.e., it is still unknown how the learning...
Chaos (Woodbury, N.Y.)
Oct 1, 2020
The problem of distinguishing deterministic chaos from non-chaotic dynamics has been an area of active research in time series analysis. Since noise contamination is unavoidable, it renders deterministic chaotic dynamics corrupted by noise to appear ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Lactate is an important biomarker with a significant diagnostic and prognostic ability in relation to life-threatening conditions and diseases such as sepsis, diabetes, cancer, pulmonary and kidney diseases, to name a few. The gold standard method fo...
Physical review letters
Mar 13, 2020
Deep neural networks are workhorse models in machine learning with multiple layers of nonlinear functions composed in series. Their loss function is highly nonconvex, yet empirically even gradient descent minimization is sufficient to arrive at accur...