arXiv · Machine Learning· Marvin van Aalst (Computational Life Science, Faculty of Mathematics and Natural Sciences, RWTH Aachen University, Germany), Ad\`ele H. Ribeiro (Causal and Explainable Artificial Intelligence in Life Sciences, Faculty of Mathematics and Natural Sciences, RWTH Aachen University, Germany, Center for Computational Life Sciences, RWTH Aachen University, Germany), Anna Matuszy\'nska (Computational Life Science, Faculty of Mathematics and Natural Sciences, RWTH Aachen University, Germany, Center for Computational Life Sciences, RWTH Aachen University, Germany)·· 8 小时前AI 评分36
当人人都能构建模型：AI 时代的机制推断
When Everyone Can Build a Model: Mechanistic Inference in the Age of AI
AI 导读
深度学习与 AI 辅助代码生成降低了生物系统数学建模的技术门槛，使研究者能够构建结合先验知识与学习结构的半机制混合模型。模型拟合良好并不意味着推断出的机制真实可靠，因数据欠定性，多个模型可能同样符合观测结果。因果推断与集成分析可分别评估因果关系的可识别性和模型行为的不确定性，帮助确定证据边界及有待验证的实验。
来源：arXiv · Machine Learning · arxiv.org