| 2024 | Evaluating the Efficacy of Large Language Models in Automating Academic Peer Reviews. | Weimin Zhao, Qusay H. Mahmoud |
| 2024 | Gaussian Process Neural Network Embeddings for Collaborative Filtering. | Wei Zhang, Brian Barr, John Paisley |
| 2024 | Spatial Transformer Network YOLO Model for Agricultural Object Detection. | Yash Vivek Zambre, Ekdev Rajkitkul, Akshatha Mohan, Joshua Peeples |
| 2024 | DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material. | Austin Yunker, Rajkumar Kettimuthu, Zachary Kral |
| 2024 | Shrinking: Reconstruction of Parameterized Surfaces from Signed Distance Fields. | Haotian Yin, Przemyslaw Musialski |
| 2024 | Finding an Optimal Small Sample of Training Dataset for Computer Vision Deep-Learning Models. | Aviv Yehezkel, Eyal Elyashiv |
| 2024 | An Efficient Approach for Enhancing GenAI Trustworthiness. | Aviv Yehezkel |
| 2024 | Deep Learning with Uncertainty Quantification for Predicting the Segmentation Dice Coefficient of Prostate Cancer Biopsy Images. | Audrey Xie, Elhoucine Elfatimi, Sambuddha Ghosal, Pratik Shah |
| 2024 | Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs. | Kishan Wimalawarne, Taro Sawaki, Motokiyo Hirayama, Takanobu Kawahara, Taiji Suzuki |
| 2024 | The Innate Curiosity in the Multi-Agent Transformer. | Arthur S. Williams, Alister Maguire, Braden Soper, Dan M. Merl |
| 2024 | Using LLMs to Establish Implicit User Sentiment of Software Desirability. | Sherri Weitl-Harms, John D. Hastings, Jonah Lum |
| 2024 | Towards Multi-Class Open-Set Recognition by Use of Lower Dimensional Latent Space Embeddings. | John G. Warner, Vishal Patel |
| 2024 | Deep Learning Based Inverse Modeling for Materials Design: From Microstructure and Property to Processing. | Kewei Wang, Yuwei Mao, Mahmudul Hasan, Md Maruf Billah, Muhammed Nur Talha Kilic, Vishu Gupta, Wei-Keng Liao, Alok N. Choudhary, Pinar Acar, Ankit Agrawal |
| 2024 | Semi-Supervised Learning and Focal Masking for Vessel Segmentation in X-Ray Coronary Angiography. | Zhewei Wang, Jundong Liu |
| 2024 | Scheduled Sampling for Recursive Multi-Step GPU Temperature Forecasting. | Harold Wang, Xunfei Jiang, Mahdi Ebrahimi |
| 2024 | LLM for Generating Simulation Inputs to Evaluate Path Planning Algorithms. | Chenyang Wang, Jonathan Diller, Qi Han |
| 2024 | Iterative Feedback-Enhanced Prompting: A Green Algorithm for Reducing Household Food Waste. | Yuekai Wang |
| 2024 | New Class Labeling and Evaluation Methodology for Balanced and Highly Imbalanced Data. | Mary Anne Walauskis, Taghi M. Khoshgoftaar |
| 2024 | WindVibraTransformer: A Foundational Model for Precise and Robust Wind Turbine Condition Monitoring via Vibration Signals. | Takuya Wakayama, Taiki Inoue, Jun Ogata, Makoto Iida, Tetsuji Ogawa |
| 2024 | Contrastive Representation Learning for Predicting Solar Flares from Extremely Imbalanced Multivariate Time Series Data. | Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi |
| 2024 | Learning Input Driven Dynamic Bayesian Networks with Measurement Noise. | Dvid Veres, Ping Li, Visakan Kadirkamanathan |
| 2024 | High-Speed Deformation Prediction in Selective Laser Melting Using Context-Adaptive Neural Networks. | Mathieu Vandecasteele, Domenico Iuso, Milad Hamidi Nasab, Dries Verhees, Joaquim G. Sanctorum, Mohsen Nourazar, Abdellatif Bey-Temsamani, Brian G. Booth |
| 2024 | Enhancing Dialogue Analysis in Multiparty Meetings Through Argument and Relation Classification Models. | Vishal Vaitla, Melody Moh, Teng-Sheng Moh |
| 2024 | Hierarchical Supervised Monte Carlo Ensemble Learning. | Ziauddin Ursani, Dmytro Antypov, Katie Atkinson, Judith Clymo, Matthew S. Dyer, Matthew J. Rosseinsky, Sven Schewe, Andrij Vasylenko |
| 2024 | The Theory of Probabilistic Hierarchical Supervised Ensemble Learning. | Ziauddin Ursani, Dmytro Antypov, Katie Atkinson, Judith Clymo, Matthew S. Dyer, Matthew J. Rosseinsky, Sven Schewe, Andrij Vasylenko |