日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

SRBench++ : principled benchmarking of symbolic regression with domain-expert interpretation

SRBench++:基于领域专家解释的符号回归原理基准测试

de Franca, F O; Virgolin, M; Kommenda, M; Majumder, M S; Cranmer, M; Espada, G; Ingelse, L; Fonseca, A; Landajuela, M; Petersen, B; Glatt, R; Mundhenk, N; Lee, C S; Hochhalter, J D; Randall, D L; Kamienny, P; Zhang, H; Dick, G; Simon, A; Burlacu, B; Kasak, Jaan; Machado, Meera; Wilstrup, Casper; La Cava, W G

The use of artificial intelligence and machine learning methods in early pregnancy pre-eclampsia screening: A systematic review protocol

人工智能和机器学习方法在妊娠早期先兆子痫筛查中的应用:系统评价方案

Hedley, Paula L; Hagen, Christian M; Wilstrup, Casper; Christiansen, Michael

Combining symbolic regression with the Cox proportional hazards model improves prediction of heart failure deaths

将符号回归与Cox比例风险模型相结合,可以提高对心力衰竭死亡的预测能力。

Wilstrup, Casper; Cave, Chris

Engaging Occupational Safety and Health Professionals in Bridging Research and Practice: Evaluation of a Participatory Workshop Program in the Danish Construction Industry

让职业安全与健康专业人员参与弥合研究与实践之间的鸿沟:丹麦建筑业参与式研讨会项目的评估

Brandt, Mikkel; Wilstrup, Ninna Maria; Jakobsen, Markus D; Van Eerd, Dwayne; Andersen, Lars L; Ajslev, Jeppe Z N