27 citations · 52 across the 8 of their papers we have counts for
11 papers
LLM-ODE: Data-driven Discovery of Dynamical Systems with Large Language Models
Amirmohammad Ziaei Bideh, Jonathan Gryak
Discovering the governing equations of dynamical systems is a central problem across many scientific disciplines. As experimental data become increasingly available, automated equa…
MDBench: Benchmarking Data-Driven Methods for Model Discovery
Amirmohammad Ziaei Bideh, Aleksandra Georgievska, Jonathan Gryak
Model discovery aims to uncover governing differential equations of dynamical systems directly from experimental data. Benchmarking such methods is essential for tracking progress…
Tensor Denoising via Amplification and Stable Rank Methods
Jonathan Gryak, Kayvan Najarian, Harm Derksen
Tensors in the form of multilinear arrays are ubiquitous in data science applications. Captured real-world data, including video, hyperspectral images, and discretized physical sys…
Prediction of Oral Food Challenge Outcomes via Ensemble Learning
Justin Zhang, Deborah Lee, Kylie Jungles +5
Oral Food Challenges (OFCs) are essential to accurately diagnosing food allergy due to the limitations of existing clinical testing. However, some patients are hesitant to undergo…
A Novel Tropical Geometry-based Interpretable Machine Learning Method: Application in Prognosis of Advanced Heart Failure
Heming Yao, Harm Derksen, Jessica R. Golbus +4
A model's interpretability is essential to many practical applications such as clinical decision support systems. In this paper, a novel interpretable machine learning method is pr…
Motion-based Camera Localization System in Colonoscopy Videos
Heming Yao, Ryan W. Stidham, Zijun Gao +2
Optical colonoscopy is an essential diagnostic and prognostic tool for many gastrointestinal diseases, including cancer screening and staging, intestinal bleeding, diarrhea, abdomi…
Algebraic Methods for Tensor Data
Neriman Tokcan, Jonathan Gryak, Kayvan Najarian +1
We develop algebraic methods for computations with tensor data. We give 3 applications: extracting features that are invariant under the orthogonal symmetries in each of the modes,…
An Unsupervised Feature Learning Approach to Reduce False Alarm Rate in ICUs
Behzad Ghazanfari, Fatemeh Afghah, Kayvan Najarian +3
The high rate of false alarms in intensive care units (ICUs) is one of the top challenges of using medical technology in hospitals. These false alarms are often caused by patients'…
Solving the Conjugacy Decision Problem via Machine Learning
Jonathan Gryak, Robert M. Haralick, Delaram Kahrobaei
Machine learning and pattern recognition techniques have been successfully applied to algorithmic problems in free groups. In this paper, we seek to extend these techniques to fini…
On the Conjugacy Problem in Certain Metabelian Groups
Jonathan Gryak, Delaram Kahrobaei, Conchita Martinez-Perez
Weanalyzethecomputationalcomplexityofanalgorithmtosolve the conjugacy search problem in a certain family of metabelian groups. We prove that in general the time complexity of the c…
The Status of Polycyclic Group-Based Cryptography: A Survey and Open Problems
Jonathan Gryak, Delaram Kahrobaei
Polycyclic groups are natural generalizations of cyclic groups but with more complicated algorithmic properties. They are finitely presented and the word, conjugacy, and isomorphis…