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ORCIDNature Machine Intelligence, Volume 5
Volume 5, Number 1, January 2023
- The AI writing on the wall. 1
- Alissa Brauneck
, Louisa Schmalhorst, Mohammad Mahdi Kazemi Majdabadi, Mohammad Bakhtiari, Uwe Völker, Christina Caroline Saak, Jan Baumbach, Linda Baumbach, Gabriele Buchholtz:
Federated machine learning in data-protection-compliant research. 2-4 - Emilia Niemiec:
A cautionary tale about the adoption of medical AI in Sweden. 5-7 - Philippe A. Robert, Victor Greiff:
Bridging the neutralization gap for unseen antibodies. 8-10 - Jesper N. Tegnér:
Translating single-cell genomics into cell types. 11-12 - Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris C. Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, Xuan Vinh Doan, David Leslie, Ginestra Bianconi, Rubén J. Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur:
Learning from data with structured missingness. 13-23 - Stefan Boettcher:
Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems. 24-25 - Martin J. A. Schuetz, J. Kyle Brubaker, Helmut G. Katzgraber:
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems. 26-28 - Maria Chiara Angelini, Federico Ricci-Tersenghi:
Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set. 29-31 - Martin J. A. Schuetz, J. Kyle Brubaker, Helmut G. Katzgraber:
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set. 32-34 - Chanseok Lee, Gookho Song, Hyeonggeon Kim, Jong Chul Ye, Mooseok Jang:
Deep learning based on parameterized physical forward model for adaptive holographic imaging with unpaired data. 35-45 - Ashish Sharma, Inna W. Lin, Adam S. Miner, David C. Atkins, Tim Althoff:
Human-AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support. 46-57 - Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton:
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes. 58-70 - Jesús Pineda, Benjamin Midtvedt, Harshith Bachimanchi, Sergio Noé, Daniel Midtvedt, Giovanni Volpe, Carlo Manzo:
Geometric deep learning reveals the spatiotemporal features of microscopic motion. 71-82 - Cheng Xue, Vimukthini Pinto, Chathura Nagoda Gamage, Ekaterina Nikonova, Peng Zhang, Jochen Renz:
Phy-Q as a measure for physical reasoning intelligence. 83-93 - Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Publisher Correction: Advancing ethics review practices in AI research. 94
Volume 5, Number 2, February 2023
- Algorithmic recommendations, anyone? 95
- Alessandro Hammond, Bhav Jain, Leo Anthony Celi, Fatima Cody Stanford:
An extension to the FDA approval process is needed to achieve AI equity. 96-97 - Annamaria Carusi, Peter D. Winter, Iain Armstrong, Fabio Ciravegna, David G. Kiely, Allan Lawrie, Haiping Lu, Ian Sabroe, Andy Swift:
Medical artificial intelligence is as much social as it is technological. 98-100 - David A. Hendrix:
Crowdsourcing to predict RNA degradation and secondary structure. 101-103 - Shaocong Wang, Yi Li, Dingchen Wang, Woyu Zhang, Xi Chen, Danian Dong, Songqi Wang, Xumeng Zhang, Peng Lin, Claudio Gallicchio, Xiaoxin Xu, Qi Liu, Kwang-Ting Cheng, Zhongrui Wang, Dashan Shang, Ming Liu:
Echo state graph neural networks with analogue random resistive memory arrays. 104-113 - Xiao Luo, Xiongbin Kang, Alexander Schönhuth:
Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks. 114-125 - Peizhen Bai, Filip Miljkovic, Bino John, Haiping Lu:
Interpretable bilinear attention network with domain adaptation improves drug-target prediction. 126-136 - Maximilian Geisslinger, Franziska Poszler, Markus Lienkamp:
An ethical trajectory planning algorithm for autonomous vehicles. 137-144 - Zhong Cao, Kun Jiang, Weitao Zhou, Shaobing Xu, Huei Peng, Diange Yang:
Continuous improvement of self-driving cars using dynamic confidence-aware reinforcement learning. 145-158 - Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee:
Estimating categorical counterfactuals via deep twin networks. 159-168 - Qisheng Yang, Weiqiu Jin, Qihang Zhang, Yuhong Wei, Zhanfeng Guo, Xiaoshi Li, Yi Yang, Qingquan Luo, He Tian, Tianling Ren:
Mixed-modality speech recognition and interaction using a wearable artificial throat. 169-180 - Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
A challenge for rounded evaluation of recommender systems. 181-182
Volume 5, Number 3, March 2023
- Space missions out of this world with AI. 183
- Nandana Sengupta, Vidya Subramanian, Anwesh Mukhopadhyay, Arul George Scaria:
A Global South perspective for ethical algorithms and the State. 184-186 - Mona Sloane, Ian Solano-Kamaiko, Jun Yuan, Aritra Dasgupta, Julia Stoyanovich:
Introducing contextual transparency for automated decision systems. 187-195 - Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes:
Biomonitoring and precision health in deep space supported by artificial intelligence. 196-207 - Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes:
Biological research and self-driving labs in deep space supported by artificial intelligence. 208-219 - Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, Jing Yi, Weilin Zhao, Xiaozhi Wang, Zhiyuan Liu, Hai-Tao Zheng, Jianfei Chen, Yang Liu, Jie Tang, Juanzi Li, Maosong Sun:
Parameter-efficient fine-tuning of large-scale pre-trained language models. 220-235 - Yicheng Gao, Yuli Gao, Yuxiao Fan, Chengyu Zhu, Zhiting Wei, Chi Zhou, Guohui Chuai, Qinchang Chen, He Zhang, Qi Liu:
Pan-Peptide Meta Learning for T-cell receptor-antigen binding recognition. 236-249 - Hugues Turbé, Mina Bjelogrlic, Christian Lovis, Gianmarco Mengaldo:
Evaluation of post-hoc interpretability methods in time-series classification. 250-260 - Delin Hu, Francesco Giorgio Serchi, Shiming Zhang, Yunjie Yang:
Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots. 261-272 - Tim Rädsch, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Nicholas Schreck, A. Emre Kavur, Bünyamin Pekdemir, Tobias Roß, Annette Kopp-Schneider, Lena Maier-Hein:
Labelling instructions matter in biomedical image analysis. 273-283 - Tong Wang, Xu-Wen Wang, Kathleen A. Lee-Sarwar, Augusto A. Litonjua, Scott T. Weiss, Yizhou Sun, Sergei Maslov, Yang-Yu Liu:
Predicting metabolomic profiles from microbial composition through neural ordinary differential equations. 284-293 - Cong Gao, Benjamin D. Killeen, Yicheng Hu, Robert B. Grupp, Russell H. Taylor, Mehran Armand, Mathias Unberath:
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis. 294-308 - Yeonghun Kang, Hyunsoo Park, Berend Smit, Jihan Kim:
A multi-modal pre-training transformer for universal transfer learning in metal-organic frameworks. 309-318 - Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting:
A typology for exploring the mitigation of shortcut behaviour. 319-330
Volume 5, Number 4, April 2023
- What's the next word in large language models? 331-332
- Silvia Milano, Joshua A. McGrane, Sabina Leonelli:
Large language models challenge the future of higher education. 333-334 - Thomas G. Day, John M. Simpson, Reza Razavi, Bernhard Kainz:
Improving image labelling quality. 335-336 - Duolin Wang, Fei He, Yang Yu, Dong Xu:
Meta-learning for T cell receptor binding specificity and beyond. 337-339 - Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik:
Multimodal learning with graphs. 340-350 - Sandra Steyaert, Marija Pizurica, Divya Nagaraj, Priya Khandelwal, Tina Hernandez-Boussard, Andrew J. Gentles, Olivier Gevaert:
Multimodal data fusion for cancer biomarker discovery with deep learning. 351-362 - Michael Hersche, Mustafa Zeqiri, Luca Benini, Abu Sebastian, Abbas Rahimi:
A neuro-vector-symbolic architecture for solving Raven's progressive matrices. 363-375 - Ying Tang, Jiayu Weng, Pan Zhang:
Neural-network solutions to stochastic reaction networks. 376-385 - Maranga Mokaya, Fergus Imrie, Willem P. van Hoorn, Aleksandra Kalisz, Anthony R. Bradley, Charlotte M. Deane:
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning. 386-394 - Xingang Peng, Yipin Lei, Peiyuan Feng, Lemei Jia, Jianzhu Ma, Dan Zhao, Jianyang Zeng:
Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning. 395-407 - Junhao Liang, Weisheng Zhang, Jianghui Yang, Meilong Wu, Qionghai Dai, Hongfang Yin, Ying Xiao, Lingjie Kong:
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer. 408-420 - Ruoqi Liu, Katherine M. Hunold, Jeffrey M. Caterino, Ping Zhang:
Estimating treatment effects for time-to-treatment antibiotic stewardship in sepsis. 421-431 - Jannis Born, Matteo Manica:
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling. 432-444 - Xiaoqi Wang, Yingjie Cheng, Yaning Yang, Yue Yu, Fei Li, Shaoliang Peng:
Multitask joint strategies of self-supervised representation learning on biomedical networks for drug discovery. 445-456 - Bin Li, Ziping Wei, Jingjing Wu, Shuai Yu, Tian Zhang, Chunli Zhu, Dezhi Zheng, Weisi Guo, Chenglin Zhao, Jun Zhang:
Machine learning-enabled globally guaranteed evolutionary computation. 457-467
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