15 citations · 29 across the 16 of their papers we have counts for
17 papers
RTS Smoother-Guided Learning of Physics-Based Neural Differential Models
Ahmet Demirkaya, Georgios Stratis, Tales Imbiriba +2
Ordinary differential equations (ODEs) are widely used to model dynamical systems in physics, biology, neuroscience, and physiology, but in many applications some equations of the…
SSplain: Sparse and Smooth Explainer for Retinopathy of Prematurity Classification
Elifnur Sunger, Tales Imbiriba, Peter Campbell +3
Neural networks are frequently used in medical diagnosis. However, due to their black-box nature, model explainers are used to help clinicians understand better and trust model out…
Hierarchical Temporal Point Process Modeling of Aggressive Behavior Onset in Psychiatric Inpatient Youth with Autism for Branching Factor Estimation
Michael Potter, Michael Everett, Deniz Erdogmus +3
Aggressive behavior in autistic inpatient youth often arises in temporally clustered bursts complicating efforts to distinguish external triggers from internal escalation. The samp…
Exploring Theory-Laden Observations in the Brain Basis of Emotional Experience
Christiana Westlin, Ashutosh Singh, Deniz Erdogmus +2
In the science of emotion, it is widely assumed that folk emotion categories form a biological and psychological typology, and studies are routinely designed and analyzed to identi…
Recursive Deep Inverse Reinforcement Learning
Paul Ghanem, Owen Howell, Michael Potter +4
Inferring an adversary's goals from exhibited behavior is crucial for counterplanning and non-cooperative multi-agent systems in domains like cybersecurity, military, and strategy…
Active Learning For Repairable Hardware Systems With Partial Coverage
Michael Potter, Beyza Kalkanlı, Deniz Erdoğmuş +1
Identifying the optimal diagnostic test and hardware system instance to infer reliability characteristics using field data is challenging, especially when constrained by fixed budg…
Temporal Point Process Modeling of Aggressive Behavior Onset in Psychiatric Inpatient Youths with Autism
Michael Potter, Michael Everett, Ashutosh Singh +6
Aggressive behavior, including aggression towards others and self-injury, occurs in up to 80% of children and adolescents with autism, making it a leading cause of behavioral healt…
Dependency-aware Maximum Likelihood Estimation for Active Learning
Beyza Kalkanli, Tales Imbiriba, Stratis Ioannidis +2
Active learning aims to efficiently build a labeled training set by strategically selecting samples to query labels from annotators. In this sequential process, each sample acquisi…
MarkovType: A Markov Decision Process Strategy for Non-Invasive Brain-Computer Interfaces Typing Systems
Elifnur Sunger, Yunus Bicer, Deniz Erdogmus +1
Brain-Computer Interfaces (BCIs) help people with severe speech and motor disabilities communicate and interact with their environment using neural activity. This work focuses on t…
Learning Physics Informed Neural ODEs With Partial Measurements
Paul Ghanem, Ahmet Demirkaya, Tales Imbiriba +3
Learning dynamics governing physical and spatiotemporal processes is a challenging problem, especially in scenarios where states are partially measured. In this work, we tackle the…
KODA: A Data-Driven Recursive Model for Time Series Forecasting and Data Assimilation using Koopman Operators
Ashutosh Singh, Ashish Singh, Tales Imbiriba +2
Approaches based on Koopman operators have shown great promise in forecasting time series data generated by complex nonlinear dynamical systems (NLDS). Although such approaches are…
Continuously Optimizing Radar Placement with Model Predictive Path Integrals
Michael Potter, Shuo Tang, Paul Ghanem +8
Continuously optimizing sensor placement is essential for precise target localization in various military and civilian applications. While information theory has shown promise in o…
Learning Semilinear Neural Operators : A Unified Recursive Framework For Prediction And Data Assimilation
Ashutosh Singh, Ricardo Augusto Borsoi, Deniz Erdogmus +1
Recent advances in the theory of Neural Operators (NOs) have enabled fast and accurate computation of the solutions to complex systems described by partial differential equations (…
Multistatic-Radar RCS-Signature Recognition of Aerial Vehicles: A Bayesian Fusion Approach
Michael Potter, Murat Akcakaya, Marius Necsoiu +3
Radar Automated Target Recognition (RATR) for Unmanned Aerial Vehicles (UAVs) involves transmitting Electromagnetic Waves (EMWs) and performing target type recognition on the recei…
Fetal-BET: Brain Extraction Tool for Fetal MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdoğmuş +1
Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it has been a very challenging task due to non-standard fetal head pose,…
Tubular Curvature Filter: Pointwise Curvature Calculation for Tubular Objects in Images
Elifnur Sunger, Beyza Kalkanli, Veysi Yildiz +4
Purpose: Accurate estimation of blood vessel tortuosity from medical images is an extremely important and challenging task. It is particularly relevant in the context of retinopath…
Learning Interpretable Deep Disentangled Neural Networks for Hyperspectral Unmixing
Ricardo Augusto Borsoi, Deniz Erdoğmuş, Tales Imbiriba
Although considerable effort has been dedicated to improving the solution to the hyperspectral unmixing problem, non-idealities such as complex radiation scattering and endmember v…