96 citations
- Northwestern UniversityUS6 papers
- University of TorontoCA2 papers
- AMA Computer UniversityPH1 paper
- Austin CollegeUS1 paper
- Canada Research ChairsCA1 paper
- Case Western Reserve UniversityUS1 paper
- Centre de Recherches sur les Macromolécules VégétalesFR1 paper
- Indian Institute of Technology RoorkeeIN1 paper
- Jersey City Medical CenterUS1 paper
- National University of SingaporeSG1 paper
- New Jersey City UniversityUS1 paper
- Northern Arizona UniversityUS1 paper
9 papers
SELDON: Supernova Explosions Learned by Deep ODE Networks
Jiezhong Wu, Jack O'Brien, Jennifer Li +6
The discovery rate of optical transients will explode to 10 million public alerts per night once the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, overw…
Uncertainty-Aware Digital Twins: Robust Model Predictive Control using Time-Series Deep Quantile Learning
Yi-Ping Chen, Ying-Kuan Tsai, Vispi Karkaria +1
Digital Twins, virtual replicas of physical systems that enable real-time monitoring, model updates, predictions, and decision-making, present novel avenues for proactive control s…
Real-Time Decision-Making for Digital Twin in Additive Manufacturing with Model Predictive Control using Time-Series Deep Neural Networks
Yi-Ping Chen, Vispi Karkaria, Ying-Kuan Tsai +5
Digital Twin -- a virtual replica of a physical system enabling real-time monitoring, model updating, prediction, and decision-making -- combined with recent advances in machine le…
Optimizing Automated Picking Systems in Warehouse Robots Using Machine Learning
Keqin Li, Jin Wang, Xubo Wu +7
With the rapid growth of global e-commerce, the demand for automation in the logistics industry is increasing. This study focuses on automated picking systems in warehouses, utiliz…
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning
Jie Chen, Pengfei Ou, Yuxin Chang +4
High-performance catalysts are crucial for sustainable energy conversion and human health. However, the discovery of catalysts faces challenges due to the absence of efficient appr…
Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +1
Knowledge distillation (KD) has demonstrated remarkable success across various domains, but its application to medical imaging tasks, such as kidney and liver tumor segmentation, h…