1 citations · 1 across the 9 of their papers we have counts for
11 papers
Cost-effective Reduced-Order Modeling via Bayesian Active Learning
Amir Hossein Rahmati, Nathan M. Urban, Byung-Jun Yoon +1
Machine Learning surrogates have been developed to accelerate solving systems dynamics of complex processes in different science and engineering applications. To faithfully capture…
Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
Nazmus Saadat As-Saquib, A N M Nafiz Abeer, Hung-Ta Chien +3
Training neural networks has traditionally relied on backpropagation (BP), a gradient-based algorithm that, despite its widespread success, suffers from key limitations in both bio…
Epidemiological Model Calibration via Graybox Bayesian Optimization
Puhua Niu, Byung-Jun Yoon, Xiaoning Qian
In this study, we focus on developing efficient calibration methods via Bayesian decision-making for the family of compartmental epidemiological models. The existing calibration me…
Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance Sampling
Xihaier Luo, Samuel Lurvey, Yi Huang +3
High-energy, large-scale particle colliders in nuclear and high-energy physics generate data at extraordinary rates, reaching up to terabyte and several petabytes per second, r…
Variable Rate Neural Compression for Sparse Detector Data
Yi Huang, Yeonju Go, Jin Huang +9
High-energy large-scale particle colliders generate data at extraordinary rates. Developing real-time high-throughput data compression algorithms to reduce data volume and meet the…
LoRA-BERT: a Natural Language Processing Model for Robust and Accurate Prediction of long non-coding RNAs
Nicholas Jeon, Xiaoning Qian, Lamin SaidyKhan +2
Long non-coding RNAs (lncRNAs) serve as crucial regulators in numerous biological processes. Although they share sequence similarities with messenger RNAs (mRNAs), lncRNAs perform…