LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes by Olivier Collier (7444844)

Real-Time Drone-Based Tomato Generative Organ Counting Model Using YOLO V5 and Deep-Sort by Yunus Egi (13273638)

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation by Xutong Li (7250720)

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation by Xutong Li (7250720)

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation by Xutong Li (7250720)

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation by Xutong Li (7250720)

NiO/ZnO Nanocomposites for Multimodal Intelligent MEMS Gas Sensors by Jiaqing Zhu (9327641)

“…These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. …”

NiO/ZnO Nanocomposites for Multimodal Intelligent MEMS Gas Sensors by Jiaqing Zhu (9327641)

“…These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. …”

NiO/ZnO Nanocomposites for Multimodal Intelligent MEMS Gas Sensors by Jiaqing Zhu (9327641)

“…These sensors demonstrate enhanced responses to ethylene glycol (EG) and limonene (LM) at different operating temperatures, demonstrating material-specific selectivity. Additionally, a multitask deep learning model is employed for real-time, quantitative detection of VOCs, accurately predicting their concentration and type. …”

Group Selection and Shrinkage: Structured Sparsity for Semiparametric Additive Models by Ryan Thompson (158538)

“…<p>Sparse regression and classification estimators that respect group structures have application to an assortment of statistical and machine learning problems, from multitask learning to sparse additive modeling to hierarchical selection. …”

BIVAS: A Scalable Bayesian Method for Bi-Level Variable Selection With Applications by Mingxuan Cai (6812147)

“…We further extend the developed method to model datasets from multitask learning. The comprehensive numerical results from both simulation studies and real data analysis demonstrate the advantages of BIVAS for variable selection, parameter estimation, and computational efficiency over existing methods. …”

Graph Neural Networks for Prediction of Fuel Ignition Quality by Artur M. Schweidtmann (3345143)

“…More specifically, GNNs learn physicochemical properties as a function of the molecular graph in a supervised learning setup using a backpropagation algorithm. …”