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ORCIDNature Machine Intelligence, Volume 7
Volume 7, Number 1, 2025
- Machine learning solutions looking for PDE problems. 1
- Johannes Brandstetter:
Envisioning better benchmarks for machine learning PDE solvers. 2-3 - Molly J. Crockett:
Modern maxims for an AI oracle. 4-5 - Hongling Zheng
, Li Shen, Anke Tang, Yong Luo, Han Hu, Bo Du, Yonggang Wen, Dacheng Tao:
Learning from models beyond fine-tuning. 6-17 - Yuqi Liu, Jing Li, Peihan Li, Yehong Yang, Kaiying Wang, Jinhui Li, Lang Yang, Jiangfeng Liu, Leili Jia, Aiping Wu, Juntao Yang, Peng Li, Hongbin Song:
ARNLE model identifies prevalence potential of SARS-CoV-2 variants. 18-28 - Shihao Ma, Andy G. X. Zeng, Benjamin Haibe-Kains, Anna Goldenberg, John E. Dick, Bo Wang:
Moving towards genome-wide data integration for patient stratification with Integrate Any Omics. 29-42 - Ismael T. Freire, Adrián Fernández Amil, Paul F. M. J. Verschure:
Sequential memory improves sample and memory efficiency in episodic control. 43-55 - Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi:
The design space of E(3)-equivariant atom-centred interatomic potentials. 56-67 - Till Richter, Mojtaba Bahrami, Yufan Xia, David S. Fischer, Fabian J. Theis:
Delineating the effective use of self-supervised learning in single-cell genomics. 68-78 - Pragalbh Vashishtha, Hitesh Gupta Kattamuri, Nikhil Thawari, Murugaiyan Amirthalingam, Rohit Batra:
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI. 79-84 - Yonghan Yu, Ming Li:
Towards highly sensitive deep learning-based end-to-end database search for tandem mass spectrometry. 85-95 - Luca M. Schulze Buschoff, Elif Akata, Matthias Bethge, Eric Schulz:
Visual cognition in multimodal large language models. 96-106 - Juan L. Gamella, Jonas Peters, Peter Bühlmann:
Causal chambers as a real-world physical testbed for AI methodology. 107-118 - Fernando Pérez-García, Harshita Sharma, Sam Bond-Taylor, Kenza Bouzid, Valentina Salvatelli, Maximilian Ilse, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Matthew P. Lungren, Maria Teodora Wetscherek, Noel Codella, Stephanie L. Hyland, Javier Alvarez-Valle, Ozan Oktay:
Exploring scalable medical image encoders beyond text supervision. 119-130 - Zhiwei Nie, Xudong Liu, Jie Chen, Zhennan Wang, Yutian Liu, Haorui Si, Tianyi Dong, Fan Xu, Guoli Song, Yu Wang, Peng Zhou, Wen Gao, Yonghong Tian:
A unified evolution-driven deep learning framework for virus variation driver prediction. 131-144 - Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Jenny T. Liang, Sydney Levine, Jesse Dodge, Keisuke Sakaguchi, Maxwell Forbes, Jack Hessel, Jonathan Borchardt, Taylor Sorensen, Saadia Gabriel, Yulia Tsvetkov, Oren Etzioni, Maarten Sap, Regina Rini, Yejin Choi:
Investigating machine moral judgement through the Delphi experiment. 145-160
Volume 7, Number 2, 2025
- Seeking visions for sustainable AI. 161
- Tanmoy Chakraborty, Koushik Sinha Deb, Himanshu Kulkarni, Sarah Masud, Suresh Bada Math, Gayatri Oke, Rajesh Sagar, Mona Sharma:
The promise of generative AI for suicide prevention in India. 162-163 - Leonie Bossert, Wulf Loh:
Why the carbon footprint of generative large language models alone will not help us assess their sustainability. 164-165 - Jakob Zeitler:
Physical benchmarks for testing algorithms. 166-167 - Paul Fogel, George Luta:
On board with COMET to improve omics prediction models. 168-169 - Li Su, Duolin Wang, Dong Xu:
Bridging peptide presentation and T cell recognition with multi-task learning. 170-171 - Xiaodan Xing, Fadong Shi, Jiahao Huang, Yinzhe Wu, Yang Nan, Sheng Zhang, Yingying Fang, Michael Roberts, Carola-Bibiane Schönlieb, Javier Del Ser, Guang Yang:
On the caveats of AI autophagy. 172-180 - Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Yuguang Yao, Chris Yuhao Liu, Xiaojun Xu, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu:
Rethinking machine unlearning for large language models. 181-194 - Takuya Akiba, Makoto Shing, Yujin Tang, Qi Sun, David Ha:
Evolutionary optimization of model merging recipes. 195-204 - Guy Davidson, Graham Todd, Julian Togelius, Todd M. Gureckis, Brenden M. Lake:
Goals as reward-producing programs. 205-220 - Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina G. Belém, Sheer Karny, Xinyue Hu, Lukas William Mayer, Padhraic Smyth:
What large language models know and what people think they know. 221-231 - Jeremy Wohlwend, Anusha Nathan, Nitan Shalon, Charles R. Crain, Rhoda Tano-Menka, Benjamin Goldberg, Emma Richards, Gaurav D. Gaiha, Regina Barzilay:
Deep learning enhances the prediction of HLA class I-presented CD8+ T cell epitopes in foreign pathogens. 232-243 - Zixu Wang, Yangyang Chen, Pengsen Ma, Zhou Yu, Jianmin Wang, Yuansheng Liu, Xiucai Ye, Tetsuya Sakurai, Xiangxiang Zeng:
Image-based generation for molecule design with SketchMol. 244-255 - Yuan Meng, Zhenshan Bing, Xiangtong Yao, Kejia Chen, Kai Huang, Yang Gao, Fuchun Sun, Alois Knoll:
Preserving and combining knowledge in robotic lifelong reinforcement learning. 256-269 - Han Zhang, Yuqi Li, Shun Zheng, Ziheng Lu, Xiaofan Gui, Wei Xu, Jiang Bian:
Battery lifetime prediction across diverse ageing conditions with inter-cell deep learning. 270-277 - Chenpeng Yu, Xing Fang, Shiye Tian, Hui Liu:
A unified cross-attention model for predicting antigen binding specificity to both HLA and TCR molecules. 278-292 - Samson Mataraso, Camilo Espinosa, David Seong, S. Momsen Reincke, Eloïse Berson, Jonathan D. Reiss, Yeasul Kim, Marc Ghanem, Chi-Hung Shu, Tomin James, Yuqi Tan, Sayane Shome, Ina A. Stelzer, Dorien Feyaerts, Ronald J. Wong, Gary M. Shaw, Martin S. Angst, Brice Gaudilliere, David K. Stevenson, Nima Aghaeepour:
A machine learning approach to leveraging electronic health records for enhanced omics analysis. 293-306 - Jaehoon Cha, Jinhae Park, Samuel Pinilla, Kyle L. Morris, Christopher S. Allen, Mark I. Wilkinson, Jeyan Thiyagalingam:
Discovering fully semantic representations via centroid- and orientation-aware feature learning. 307-314 - Pengfei Liu, Jun Tao, Zhixiang Ren:
A quantitative analysis of knowledge-learning preferences in large language models in molecular science. 315-327 - Julian Büchel, Giacomo Camposampiero, Athanasios Vasilopoulos, Corey Lammie, Manuel Le Gallo, Abbas Rahimi, Abu Sebastian:
Author Correction: Kernel approximation using analogue in-memory computing. 328
Volume 7, Number 3, 2025
- Transparency (in training data) is what we want. 329
- Ming Yin:
Bridging the gap between machine confidence and human perceptions. 330-331 - Alexander Schönhuth:
From data chaos to precision medicine. 332-333 - Mona Sloane, Emanuel Moss, Susan Kennedy, Matthew Stewart, Pete Warden, Brian Plancher, Vijay Janapa Reddi:
Materiality and risk in the age of pervasive AI sensors. 334-345 - Micaela E. Consens, Cameron Dufault, Michael Wainberg, Duncan Forster, Mehran Karimzadeh, Hani Goodarzi, Fabian J. Theis, Alan Moses, Bo Wang:
Transformers and genome language models. 346-362 - Philipp Hess, Michael Aich, Baoxiang Pan, Niklas Boers:
Fast, scale-adaptive and uncertainty-aware downscaling of Earth system model fields with generative machine learning. 363-373 - Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli:
Quantum circuit optimization with AlphaTensor. 374-385 - Francesco Stella, Mickaël M. Achkar, Cosimo Della Santina, Josie Hughes:
Synergy-based robotic quadruped leveraging passivity for natural intelligence and behavioural diversity. 386-399 - Angelina Wang, Jamie Morgenstern, John P. Dickerson:
Large language models that replace human participants can harmfully misportray and flatten identity groups. 400-411 - Jacob R. Kauffmann, Jonas Dippel, Lukas Ruff, Wojciech Samek, Klaus-Robert Müller, Grégoire Montavon:
Explainable AI reveals Clever Hans effects in unsupervised learning models. 412-422 - Thierry Hanser, Ernst Ahlberg, Alexander Amberg, Lennart T. Anger, Chris Barber, Richard J. Brennan, Alessandro Brigo, Annie Delaunois, Susanne Glowienke, Nigel Greene, Laura Johnston, Daniel Kuhn, Lara Kuhnke, Jean-François Marchaland, Wolfgang Muster, Jeffrey Plante, Friedrich Rippmann, Yogesh Sabnis, K. Friedemann Schmidt, Ruud van Deursen, Stéphane Werner, Angela White, Joerg Wichard, Tomoya Yukawa:
Data-driven federated learning in drug discovery with knowledge distillation. 423-436 - Yizhen Zheng, Huan Yee Koh, Jiaxin Ju, Anh T. N. Nguyen, Lauren T. May, Geoffrey I. Webb, Shirui Pan:
Large language models for scientific discovery in molecular property prediction. 437-447 - Shicheng Chen, Odin Zhang, Chenran Jiang, Huifeng Zhao, Xujun Zhang, Mengting Chen, Yun Liu, Qun Su, Zhenxing Wu, Xinyue Wang, Wanglin Qu, Yuanyi Ye, Xin Chai, Ning Wang, Tianyue Wang, Yuan An, Guanlin Wu, Qianqian Yang, Jiean Chen, Wei Xie, Haitao Lin, Dan Li, Chang-Yu Hsieh, Yong Huang, Yu Kang, Tingjun Hou, Peichen Pan:
Deep lead optimization enveloped in protein pocket and its application in designing potent and selective ligands targeting LTK protein. 448-458 - Robin Jeanne Kirschner, Kübra Karacan, Alessandro Melone, Sami Haddadin:
Categorizing robots by performance fitness into the tree of robots. 459-470 - Jiajun Zhu, Siqi Miao, Rex Ying, Pan Li:
Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning. 471-483 - Yuhang Hu, Jiong Lin, Hod Lipson:
Teaching robots to build simulations of themselves. 484-494 - Jesus de la Fuente Cedeño, Guillermo Serrano, Uxía Veleiro, Mikel Casals, Laura Vera, Marija Pizurica, Nuria Gómez-Cebrián, Leonor Puchades-Carrasco, Antonio Pineda-Lucena, Idoia Ochoa, Silve Vicent, Olivier Gevaert, Mikel Hernaez:
Towards a more inductive world for drug repurposing approaches. 495-508 - Shukai Gu, Chao Shen, Xujun Zhang, Huiyong Sun, Heng Cai, Hao Luo, Huifeng Zhao, Bo Liu, Hongyan Du, Yihao Zhao, Chenggong Fu, Silong Zhai, Yafeng Deng, Huanxiang Liu, Tingjun Hou, Yu Kang:
Benchmarking AI-powered docking methods from the perspective of virtual screening. 509-520
Volume 7, Number 4, 2025
- Robot planning with LLMs. 521
- Tapabrata Chakraborti, Christopher R. S. Banerji, Ariane Marandon, Vicky Hellon, Robin Mitra, Brieuc Lehmann, Leandra Bräuninger, Sarah F. McGough, Cagatay Turkay, Alejandro F. Frangi, Ginestra Bianconi, Weizi Li, Owen Rackham, Deepak Parashar, Chris Harbron, Ben D. MacArthur:
Personalized uncertainty quantification in artificial intelligence. 522-530 - Balint Gyevnar, Atoosa Kasirzadeh:
AI safety for everyone. 531-542 - Sheng Gong, Yumin Zhang, Zhenliang Mu, Zhichen Pu, Hongyi Wang, Xu Han, Zhiao Yu, Mengyi Chen, Tianze Zheng, Zhi Wang, Lifei Chen, Zhenze Yang, Xiaojie Wu, Shaochen Shi, Weihao Gao, Wen Yan, Liang Xiang:
A predictive machine learning force-field framework for liquid electrolyte development. 543-552 - Xingzhou Du, Yibin Wang, Junhui Law, Kaiwen Fang, Hui Chen, Yuezhen Liu, Jiangfan Yu:
Active exploration and reconstruction of vascular networks using microrobot swarms. 553-564 - Kevin Eloff, Konstantinos Kalogeropoulos, Amandla Mabona, Oliver Morell, Rachel Catzel, Esperanza Rivera-de-Torre, Jakob Berg Jespersen, Wesley Williams, Sam P. B. van Beljouw, Marcin J. Skwark, Andreas Hougaard Laustsen, Stan J. J. Brouns, Anne Ljungars, Erwin M. Schoof, Jeroen Van Goey, Ulrich auf dem Keller, Karim Beguir, Nicolás López Carranza, Timothy P. Jenkins:
InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments. 565-579 - Shengchao Liu, Yanjing Li, Zhuoxinran Li, Anthony Gitter, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Arvind Ramanathan, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar:
A text-guided protein design framework. 580-591 - Ruaridh Mon-Williams, Gen Li, Ran Long, Wenqian Du, Christopher G. Lucas:
Embodied large language models enable robots to complete complex tasks in unpredictable environments. 592-601 - Yuan Zhang, Xin Sui, Feng Pan, Kaixian Yu, Keqiao Li, Shubo Tian, Arslan Erdengasileng, Qing Han, Wanjing Wang, Jianan Wang, Jian Wang, Donghu Sun, Henry Chung, Jun Zhou, Eric Zhou, Ben Lee, Peili Zhang, Xing Qiu, Tingting Zhao, Jinfeng Zhang:
A comprehensive large-scale biomedical knowledge graph for AI-powered data-driven biomedical research. 602-614 - Chenru Duan, Guan-Horng Liu, Yuanqi Du, Tianrong Chen, Qiyuan Zhao, Haojun Jia, Carla P. Gomes, Evangelos A. Theodorou, Heather J. Kulik:
Optimal transport for generating transition states in chemical reactions. 615-626 - Jian Tang, Yi Zhu, Gai Jiang, Lin Xiao, Wei Ren, Yu Zhou, Qinying Gu, Biao Yan, Jiayi Zhang, Hengchang Bi, Xing Wu, Zhiyong Fan, Leilei Gu:
Human-centred design and fabrication of a wearable multimodal visual assistance system. 627-638 - Daniella Bar-Lev, Itai Orr, Omer Sabary, Tuvi Etzion, Eitan Yaakobi:
Scalable and robust DNA-based storage via coding theory and deep learning. 639-649 - Yunxiang Zhao, Jijun Yu, Yixin Su, You Shu, Enhao Ma, Jing Wang, Shuyang Jiang, Congwen Wei, Dongsheng Li, Zhen Huang, Gong Cheng, Hongguang Ren, Jiannan Feng:
A unified deep framework for peptide-major histocompatibility complex-T cell receptor binding prediction. 650-660 - Huixin Zhan, Jason H. Moore, Zijun Zhang:
A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics. 661-671 - Iksung Kang, Qinrong Zhang, Stella X. Yu, Na Ji:
Author Correction: Coordinate-based neural representations for computational adaptive optics in widefield microscopy. 672 - Samson Mataraso, Camilo Espinosa, David Seong, S. Momsen Reincke, Eloïse Berson, Jonathan D. Reiss, Yeasul Kim, Marc Ghanem, Chi-Hung Shu, Tomin James, Yuqi Tan, Sayane Shome, Ina A. Stelzer, Dorien Feyaerts, Ronald J. Wong, Gary M. Shaw, Martin S. Angst, Brice Gaudilliere, David K. Stevenson, Nima Aghaeepour:
Author Correction: A machine learning approach to leveraging electronic health records for enhanced omics analysis. 673
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