{"total":23,"rows":[{"id":"2309.07930","title":"Generative AI","created":"2023-09-13","cited_by_count":120,"area":null},{"id":"2409.03668","title":"A Fused Large Language Model for Predicting Startup Success","created":"2024-09-05","cited_by_count":13,"area":null},{"id":"2403.10168","title":"Explainability through uncertainty: Trustworthy decision-making with neural networks","created":"2024-03-15","cited_by_count":12,"area":null},{"id":"2303.08516","title":"Fair Off-Policy Learning from Observational Data","created":"2023-03-15","cited_by_count":11,"area":null},{"id":"2401.03244","title":"Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process","created":"2024-01-06","cited_by_count":11,"area":null},{"id":"2110.08975","title":"Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research","created":"2021-10-18","cited_by_count":7,"area":null},{"id":"2204.09123","title":"GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints","created":"2022-04-19","cited_by_count":6,"area":null},{"id":"2205.10535","title":"Deep Learning vs. Gradient Boosting: Benchmarking state-of-the-art machine learning algorithms for credit scoring","created":"2022-05-21","cited_by_count":6,"area":null},{"id":"2111.12140","title":"Filter Methods for Feature Selection in Supervised Machine Learning Applications -- Review and Benchmark","created":"2021-11-23","cited_by_count":4,"area":null},{"id":"2403.10182","title":"Fast and reliable uncertainty quantification with neural network ensembles for industrial image classification","created":"2024-03-15","cited_by_count":4,"area":null},{"id":"2111.13760","title":"Interpreting Machine Learning Models for Room Temperature Prediction in Non-domestic Buildings","created":"2021-11-23","cited_by_count":2,"area":null},{"id":"2208.03937","title":"Detecting User Exits from Online Behavior: A Duration-Dependent Latent State Model","created":"2022-08-08","cited_by_count":2,"area":null},{"id":"2212.12407","title":"Text classification in shipping industry using unsupervised models and Transformer based supervised models","created":"2022-12-21","cited_by_count":1,"area":null},{"id":"2405.13187","title":"A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis","created":"2024-05-21","cited_by_count":1,"area":null},{"id":"2601.16568","title":"Predicting Startup Success Using Large Language Models: A Novel In-Context Learning Approach","created":"2026-01-23","cited_by_count":1,"area":null},{"id":"2201.02028","title":"A Light in the Dark: Deep Learning Practices for Industrial Computer Vision","created":"2022-01-06","cited_by_count":0,"area":null},{"id":"2302.10434","title":"Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes","created":"2023-02-21","cited_by_count":0,"area":null},{"id":"2306.00380","title":"Survey of Trustworthy AI: A Meta Decision of AI","created":"2023-06-01","cited_by_count":0,"area":null},{"id":"2309.12620","title":"Data-driven Preference Learning Methods for Sorting Problems with Multiple Temporal Criteria","created":"2023-09-22","cited_by_count":0,"area":null},{"id":"2310.17915","title":"Lifting the Veil: Unlocking the Power of Depth in Q-learning","created":"2023-10-27","cited_by_count":0,"area":null},{"id":"2310.19124","title":"Good Tools are Half the Work: Tool Usage in Deep Learning Projects","created":"2023-10-29","cited_by_count":0,"area":null},{"id":"2310.20545","title":"Optimizing accuracy and diversity: a multi-task approach to forecast combinations","created":"2023-10-31","cited_by_count":0,"area":null},{"id":"2406.12992","title":"Additive regularization schedule for neural architecture search","created":"2024-06-18","cited_by_count":0,"area":null}],"next_cursor":null}