- Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj, Maxim Raginsky. Generalization Bounds: Perspectives from Information Theory and PAC-Bayes. Foundations and Trends in Machine Learning, 18(1):1-223, 2025.
- Saurabh Kumar 0004, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy. Continual Learning as Computationally Constrained Reinforcement Learning. Foundations and Trends in Machine Learning, 18(5):913-1053, 2025.
- Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson. A Tutorial on Meta-Reinforcement Learning. Foundations and Trends in Machine Learning, 18(2-3):224-384, 2025.
- Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu 0003, Yaochen Xie, Meng Liu 0015, Yuchao Lin, Zhao Xu 0005, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu 0005, Yuqing Xie 0006, Xiang Fu 0005, Shenglong Xu, Yi Liu 0059, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang 0086, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji 0001, Jimeng Sun 0001, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji. Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Foundations and Trends in Machine Learning, 18(4):385-912, 2025.
- David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys. AutonoML: Towards an Integrated Framework for Autonomous Machine Learning. Foundations and Trends in Machine Learning, 17(4):590-766, 2024.
- Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys. Automated Deep Learning: Neural Architecture Search Is Not the End. Foundations and Trends in Machine Learning, 17(5):767-920, 2024.
- Andrea Montanari, Subhabrata Sen. A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists. Foundations and Trends in Machine Learning, 17(1):1-173, 2024.
- George H. Chen. An Introduction to Deep Survival Analysis Models for Predicting Time-to-Event Outcomes. Foundations and Trends in Machine Learning, 17(6):921-1100, 2024.
- Drago Plecko, Elias Bareinboim. Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning. Foundations and Trends in Machine Learning, 17(3):304-589, 2024.
- Pierre Alquier. User-friendly Introduction to PAC-Bayes Bounds. Foundations and Trends in Machine Learning, 17(2):174-303, 2024.