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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, John 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, John 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
Volume 5, Number 5, May 2023
- Marcello Ienca:
Don't pause giant AI for the wrong reasons. 470-471 - Sebastian Porsdam Mann, Brian D. Earp, Sven Nyholm, John Danaher, Nikolaj Møller, Hilary Bowman-Smart, Joshua Hatherley, Julian Koplin, Monika Plozza, Daniel Rodger, Peter V. Treit, Gregory Renard, John McMillan, Julian Savulescu:
Generative AI entails a credit-blame asymmetry. 472-475 - Elle Lett, William G. La Cava:
Translating intersectionality to fair machine learning in health sciences. 476-479 - Kristin M. Kostick-Quenet, Vasiliki Nataly Rahimzadeh:
Ethical hazards of health data governance in the metaverse. 480-482 - Bahare Fatemi, Jonathan Halcrow, Khuloud Jaqaman:
Geometric deep learning of particle motion by MAGIK. 483-484 - Mai Ha Vu, Rahmad Akbar, Philippe A. Robert, Bartlomiej Swiatczak, Geir Kjetil Sandve, Victor Greiff, Dag Trygve Truslew Haug:
Linguistically inspired roadmap for building biologically reliable protein language models. 485-496 - Luc Rocher, Arnaud Tournier, Yves-Alexandre de Montjoye:
Adversarial competition and collusion in algorithmic markets. 497-504 - Jiaming Liang, Chao Xu, Shengze Cai:
Recurrent graph optimal transport for learning 3D flow motion in particle tracking. 505-517 - Bojian Yin, Federico Corradi, Sander M. Bohté:
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time. 518-527 - Tao Ren, Canping Chen, Alexey V. Danilov, Susan Liu, Xiangnan Guan, Shunyi Du, Xiwei Wu, Mara H. Sherman, Paul T. Spellman, Lisa M. Coussens, Andrew C. Adey, Gordon B. Mills, Ling-Yun Wu, Zheng Xia:
Supervised learning of high-confidence phenotypic subpopulations from single-cell data. 528-541 - Yin Fang, Qiang Zhang, Ningyu Zhang, Zhuo Chen, Xiang Zhuang, Xin Shao, Xiaohui Fan, Huajun Chen:
Knowledge graph-enhanced molecular contrastive learning with functional prompt. 542-553 - Zhenge Jia, Dawei Li, Xiaowei Xu, Na Li, Feng Hong, Lichuan Ping, Yiyu Shi:
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter-defibrillators. 554-555
Volume 5, Number 6, June 2023
- A touch of virtual reality. 557
- Tanmoy Chakraborty, Sarah Masud:
Judging the creative prowess of AI. 558 - Zihao Li:
Why the European AI Act transparency obligation is insufficient. 559-560 - Francesco Stella, Cosimo Della Santina, Josie Hughes:
How can LLMs transform the robotic design process? 561-564 - Katy Ilonka Gero, Payel Das, Pierre L. Dognin, Inkit Padhi, Prasanna Sattigeri, Kush R. Varshney:
The incentive gap in data work in the era of large models. 565-567 - Joshua Goldwag, Ge Wang:
DishBrain plays Pong and promises more. 568-569 - Manuel Beiran, Camille A. Spencer-Salmon, Kanaka Rajan:
A 'programming' framework for recurrent neural networks. 570-571 - Achuta Kadambi, Celso de Melo, Cho-Jui Hsieh, Mani B. Srivastava, Stefano Soatto:
Incorporating physics into data-driven computer vision. 572-580 - Maxwell T. West, Shu Lok Tsang, Jia Shun Low, Charles D. Hill, Christopher Leckie, Lloyd C. L. Hollenberg, Sarah M. Erfani, Muhammad Usman:
Towards quantum enhanced adversarial robustness in machine learning. 581-589 - Hugh Chen, Ian C. Covert, Scott M. Lundberg, Su-In Lee:
Algorithms to estimate Shapley value feature attributions. 590-601 - Haixu Wu, Hang Zhou, Mingsheng Long, Jianmin Wang:
Interpretable weather forecasting for worldwide stations with a unified deep model. 602-611 - Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik:
Structure-inducing pre-training. 612-621 - Jason Z. Kim, Dani S. Bassett:
A neural machine code and programming framework for the reservoir computer. 622-630 - Noah Cohen Kalafut, Xiang Huang, Daifeng Wang:
Joint variational autoencoders for multimodal imputation and embedding. 631-642 - Zhuang Zhang, Zhenghao Xu, Luoqian Emu, Pingdong Wei, Sentao Chen, Zirui Zhai, Lingyu Kong, Yong Wang, Hanqing Jiang:
Active mechanical haptics with high-fidelity perceptions for immersive virtual reality. 643-655 - Tiepeng Liao, Zihao Ren, Zhaoliang Chai, Man Yuan, Chenjian Miao, Junjie Li, Qi Chen, Zhilin Li, Ziyi Wang, Lin Yi, Siyuan Ge, Wenwei Qian, Longfeng Shen, Zilei Wang, Wei Xiong, Hongying Zhu:
A super-resolution strategy for mass spectrometry imaging via transfer learning. 656-668 - Christoph H. Belke, Kevin Holdcroft, Alexander Sigrist, Jamie Paik:
Morphological flexibility in robotic systems through physical polygon meshing. 669-675 - Tao Ren, Canping Chen, Alexey V. Danilov, Susan Liu, Xiangnan Guan, Shunyi Du, Xiwei Wu, Mara H. Sherman, Paul T. Spellman, Lisa M. Coussens, Andrew C. Adey, Gordon B. Mills, Ling-Yun Wu, Zheng Xia:
Author Correction: Supervised learning of high-confidence phenotypic subpopulations from single-cell data. 676
Volume 5, Number 7, July 2023
- Language models and linguistic theories beyond words. 677-678
- Filippo Menczer, David J. Crandall, Yong-Yeol Ahn, Apu Kapadia:
Addressing the harms of AI-generated inauthentic content. 679-680 - Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb:
Navigating the development challenges in creating complex data systems. 681-686 - Zhenge Jia, Jianxu Chen, Xiaowei Xu, John N. Kheir, Jingtong Hu, Han Xiao, Sui Peng, Xiaobo Sharon Hu, Danny Ziyi Chen, Yiyu Shi:
The importance of resource awareness in artificial intelligence for healthcare. 687-698 - Addie Woicik, Mingxin Zhang, Janelle Chan, Jianzhu Ma, Sheng Wang:
Extrapolating heterogeneous time-series gene expression data using Sagittarius. 699-713 - Yudeng Lin, Qingtian Zhang, Bin Gao, Jianshi Tang, Peng Yao, Chongxuan Li, Shiyu Huang, Zhengwu Liu, Ying Zhou, Yuyi Liu, Wenqiang Zhang, Jun Zhu, He Qian, Huaqiang Wu:
Uncertainty quantification via a memristor Bayesian deep neural network for risk-sensitive reinforcement learning. 714-723 - Himashi Peiris, Munawar Hayat, Zhaolin Chen, Gary F. Egan, Mehrtash Harandi:
Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation. 724-738 - Ramón Viñas, Chaitanya K. Joshi, Dobrik Georgiev, Phillip Lin, Bianca Dumitrascu, Eric R. Gamazon, Pietro Liò:
Hypergraph factorization for multi-tissue gene expression imputation. 739-753 - Hilbert Yuen In Lam, Robbe Pincket, Hao Han, Xing Er Ong, Zechen Wang, Jamie Hinks, Yanjie Wei, Weifeng Li, Liangzhen Zheng, Yuguang Mu:
Application of variational graph encoders as an effective generalist algorithm in computer-aided drug design. 754-764 - Chengping Rao, Pu Ren, Qi Wang, Oral Buyukozturk, Hao Sun, Yang Liu:
Encoding physics to learn reaction-diffusion processes. 765-779 - Friederike Metz, Marin Bukov:
Self-correcting quantum many-body control using reinforcement learning with tensor networks. 780-791 - Emily So, Fengqing Yu, Bo Wang, Benjamin Haibe-Kains:
Reusability report: Evaluating reproducibility and reusability of a fine-tuned model to predict drug response in cancer patient samples. 792-798 - Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson:
Federated benchmarking of medical artificial intelligence with MedPerf. 799-810 - Jason Z. Kim, Dani S. Bassett:
Publisher Correction: A neural machine code and programming framework for the reservoir computer. 811
Volume 5, Number 8, August 2023
- Seeking a quantum advantage for machine learning. 813
- Lando Kirchmair, Norbert Paulo:
Taking ethics seriously in AV trajectory planning algorithms. 814-815 - Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins:
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. 816-817 - Fabian Ferrari, José van Dijck, Antal van den Bosch:
Foundation models and the privatization of public knowledge. 818-820 - W. Nicholson Price, Mark P. Sendak, Suresh Balu, Karandeep Singh:
Enabling collaborative governance of medical AI. 821-823 - Fergus Imrie, Robert Davis, Mihaela van der Schaar:
Multiple stakeholders drive diverse interpretability requirements for machine learning in healthcare. 824-829 - Catherine Bouchard, Theresa Wiesner, Andréanne Deschênes, Anthony Bilodeau, Benoît Turcotte, Christian Gagné, Flavie Lavoie-Cardinal:
Resolution enhancement with a task-assisted GAN to guide optical nanoscopy image analysis and acquisition. 830-844 - Yi Wang, Hui Tang, Lichao Huang, Lulu Pan, Lixiang Yang, Huanming Yang, Feng Mu, Meng Yang:
Self-play reinforcement learning guides protein engineering. 845-860 - Benjamin Alexander Albert, Yunxiao Yang, Xiaoshan M. Shao, Dipika Singh, Kellie N. Smith, Valsamo Anagnostou, Rachel Karchin:
Deep neural networks predict class I major histocompatibility complex epitope presentation and transfer learn neoepitope immunogenicity. 861-872 - Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju, Sameer Singh:
Explaining machine learning models with interactive natural language conversations using TalkToModel. 873-883 - Jenny Yang, Andrew A. S. Soltan, David W. Eyre, David A. Clifton:
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning. 884-894 - Luzhe Huang, Hanlong Chen, Tairan Liu, Aydogan Ozcan:
Self-supervised learning of hologram reconstruction using physics consistency. 895-907 - Yu Feng, Wei Zhang, Yuhai Tu:
Activity-weight duality in feed-forward neural networks reveals two co-determinants for generalization. 908-918 - Wanming Yu, Chuanyu Yang, Christopher McGreavy, Eleftherios Triantafyllidis, Guillaume Bellegarda, Milad Shafiee, Auke Jan Ijspeert, Zhibin Li:
Identifying important sensory feedback for learning locomotion skills. 919-932 - Karishma D'sa, James R. Evans, Gurvir S. Virdi, Giulia Vecchi, Alexander Adam, Ottavia Bertolli, James Fleming, Hojong Chang, Craig Leighton, Mathew H. Horrocks, Dilan Athauda, Minee L. Choi, Sonia Gandhi:
Prediction of mechanistic subtypes of Parkinson's using patient-derived stem cell models. 933-946 - Yi Wang, Hui Tang, Lichao Huang, Lulu Pan, Lixiang Yang, Huanming Yang, Feng Mu, Meng Yang:
Author Correction: Self-play reinforcement learning guides protein engineering. 947
Volume 5, Number 9, September 2023
- Unlocking biomolecular intelligence. 949
- Ali S. Tejani, Michail E. Klontzas, Anthony A. Gatti, John Mongan, Linda Moy, Seong Ho Park, Charles E. Kahn:
Updating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for reporting AI research. 950-951 - Tal Golan, Matthew Siegelman, Nikolaus Kriegeskorte, Christopher Baldassano:
Testing the limits of natural language models for predicting human language judgements. 952-964 - Samuel Goldman, Jeremy Wohlwend, Martin Strazar, Guy Haroush, Ramnik J. Xavier, Connor W. Coley:
Annotating metabolite mass spectra with domain-inspired chemical formula transformers. 965-979 - Yan Zhao, Shuting Cao, Yue Wang, Fan Li, Lixuan Lin, Linjie Guo, Fei Wang, Jie Chao, Xiaolei Zuo, Ying Zhu, Lihua Wang, Jiang Li, Chunhai Fan:
A temporally resolved DNA framework state machine in living cells. 980-990 - Eleftherios Triantafyllidis, Fernando Acero, Zhaocheng Liu, Zhibin Li:
Hybrid hierarchical learning for solving complex sequential tasks using the robotic manipulation network ROMAN. 991-1005 - Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin:
From attribution maps to human-understandable explanations through Concept Relevance Propagation. 1006-1019 - Odin Zhang, Jintu Zhang, Jieyu Jin, Xujun Zhang, Renling Hu, Chao Shen, Hanqun Cao, Hongyan Du, Yu Kang, Yafeng Deng, Furui Liu, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou:
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling. 1020-1030 - Bowen Deng, Peichen Zhong, KyuJung Jun, Janosh Riebesell, Kevin Han, Christopher J. Bartel, Gerbrand Ceder:
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling. 1031-1041 - Vitalii Stebliankin, Azam Shirali, Prabin Baral, Jimeng Shi, Prem Chapagain, Kalai Mathee, Giri Narasimhan:
Evaluating protein binding interfaces with transformer networks. 1042-1053
Volume 5, Number 10, October 2023
- AI reality check. 1055
- Johannes Sedlmeir, Alexander Rieger, Tamara Roth, Gilbert Fridgen:
Battling disinformation with cryptography. 1056-1057 - Ying Lu, Shi-Ju Ran:
Many-body control with reinforcement learning and tensor networks. 1058-1059 - Ceder Dens, Kris Laukens, Wout Bittremieux, Pieter Meysman:
The pitfalls of negative data bias for the T-cell epitope specificity challenge. 1060-1062 - Yicheng Gao, Yuli Gao, Kejing Dong, Siqi Wu, Qi Liu:
Reply to: The pitfalls of negative data bias for the T-cell epitope specificity challenge. 1063-1065 - Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active learning for optimal intervention design in causal models. 1066-1075 - Pat Pataranutaporn, Ruby Liu, Ed Finn, Pattie Maes:
Influencing human-AI interaction by priming beliefs about AI can increase perceived trustworthiness, empathy and effectiveness. 1076-1086 - Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He, Dayong Lin, Yingfei Xiang, Kunrui Zhu, Xiaonan Zhang, Hua Wu, Hui Li, Le Song:
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model. 1087-1096 - Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin, Ori Kabeli, Jean-Rémi King:
Decoding speech perception from non-invasive brain recordings. 1097-1107 - Duncan C. McElfresh, Christian Kroer, Sergey Pupyrev, Eric Sodomka, Karthik Abinav Sankararaman, Zack Chauvin, Neil Dexter, John P. Dickerson:
Matching algorithms for blood donation. 1108-1118 - Ziyang Zheng, Zhengyang Duan, Hang Chen, Rui Yang, Sheng Gao, Haiou Zhang, Hongkai Xiong, Xing Lin:
Dual adaptive training of photonic neural networks. 1119-1129 - Christoph Dehner, Guillaume Zahnd, Vasilis Ntziachristos, Dominik Jüstel:
A deep neural network for real-time optoacoustic image reconstruction with adjustable speed of sound. 1130-1141 - Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel:
Improving Wikipedia verifiability with AI. 1142-1148 - Mengli Sui, Yiming Ouyang, Hu Jin, Zhenyi Chai, Changyang Wei, Jiyu Li, Min Xu, Weihua Li, Liu Wang, Shiwu Zhang:
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills. 1149-1160 - Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos E. Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin:
A taxonomy and review of generalization research in NLP. 1161-1174
Volume 5, Number 11, November 2023
- A social network for AI. 1175
- Charlotte Debus, Marie Piraud, Achim Streit, Fabian J. Theis, Markus Götz:
Reporting electricity consumption is essential for sustainable AI. 1176-1178 - Sergey D. Stavisky, Maitreyee Wairagkar:
Listening in to perceived speech with contrastive learning. 1179-1180 - Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo:
A social path to human-like artificial intelligence. 1181-1188 - Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas, Krishna Murthy Jatavallabhula, Cengiz Öztireli, Tzu-Mao Li, Derek Nowrouzezahrai:
Differentiable visual computing for inverse problems and machine learning. 1189-1199 - Gefei Wang, Jia Zhao, Yan Yan, Yang Wang, Angela Ruohao Wu, Can Yang:
Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks. 1200-1213 - Jinghua Piao, Jiazhen Liu, Fang Zhang, Jun Su, Yong Li:
Human-AI adaptive dynamics drives the emergence of information cocoons. 1214-1224 - Kangyu Ji, Weizhe Lin, Yuqi Sun, Lin-Song Cui, Javad Shamsi, Yu-Hsien Chiang, Jiawei Chen, Elizabeth M. Tennyson, Linjie Dai, Qingbiao Li, Kyle Frohna, Miguel Anaya, Neil C. Greenham, Samuel D. Stranks:
Self-supervised deep learning for tracking degradation of perovskite light-emitting diodes with multispectral imaging. 1225-1235 - Fang Wang, Fan Yang, Longkai Huang, Wei Li, Jiangning Song, Robin B. Gasser, Ruedi Aebersold, Guohua Wang, Jianhua Yao:
Deep domain adversarial neural network for the deconvolution of cell type mixtures in tissue proteome profiling. 1236-1249 - Zeping Mao, Ruixue Zhang, Lei Xin, Ming Li:
Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model. 1250-1260 - Feng Liu, Shuhong Huang, Jiongsong Hu, Xiaozhou Chen, Ziguo Song, Junguo Dong, Yao Liu, Xingxu Huang, Shengqi Wang, Xiaolong Wang, Wenjie Shu:
Design of prime-editing guide RNAs with deep transfer learning. 1261-1274 - Peicong Lin, Huanyu Tao, Hao Li, Sheng-You Huang:
Protein-protein contact prediction by geometric triangle-aware protein language models. 1275-1284 - Debojyoti Biswas, Andrew G. Lamperski, Yu Yang, Kathleen Hoffman, John Guckenheimer, Eric S. Fortune, Noah J. Cowan:
Mode switching in organisms for solving explore-versus-exploit problems. 1285-1296 - Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally:
Neural scaling of deep chemical models. 1297-1305 - Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee:
Deep learning of causal structures in high dimensions under data limitations. 1306-1316 - Javier E. Santos, Zachary R. Fox, Arvind Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers:
Development of the Senseiver for efficient field reconstruction from sparse observations. 1317-1325 - Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp:
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. 1326-1335
Volume 5, Number 12, December 2023
- A year of racing ahead with AI and not breaking things. 1337
- Fernando P. Santos:
How to break information cocoons. 1338-1339 - Andrey Gromov:
Deconstructing the generalization gap. 1340-1341 - Filip Milisav, Bratislav Misic:
Spatially embedded neuromorphic networks. 1342-1343 - Changhao Xu, Samuel A. Solomon, Wei Gao:
Artificial intelligence-powered electronic skin. 1344-1355 - Liyuan Wang, Xingxing Zhang, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, Yi Zhong:
Incorporating neuro-inspired adaptability for continual learning in artificial intelligence. 1356-1368 - Jascha Achterberg, Danyal Akarca, D. J. Strouse, John Duncan, Duncan E. Astle:
Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings. 1369-1381 - Meng Liu, Tamal K. Dey, David F. Gleich:
Topological structure of complex predictions. 1382-1389 - Yunan Luo, Yang Liu, Jian Peng:
Calibrated geometric deep learning improves kinase-drug binding predictions. 1390-1401 - Kai Yuan, Noor Sajid, Karl J. Friston, Zhibin Li:
Hierarchical generative modelling for autonomous robots. 1402-1414 - Aria Y. Wang, Kendrick N. Kay, Thomas Naselaris, Michael J. Tarr, Leila Wehbe:
Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset. 1415-1426 - Andrea Mastropietro, Giuseppe Pasculli, Jürgen Bajorath:
Learning characteristics of graph neural networks predicting protein-ligand affinities. 1427-1436 - Sumeer Ahmad Khan, Alberto Maillo, Vincenzo Lagani, Robert Lehmann, Narsis A. Kiani, David Gomez-Cabrero, Jesper Tegnér:
Reusability report: Learning the transcriptional grammar in single-cell RNA-sequencing data using transformers. 1437-1446 - Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar:
Multi-modal molecule structure-text model for text-based retrieval and editing. 1447-1457 - Raphaël Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson:
Physics-enhanced deep surrogates for partial differential equations. 1458-1465 - Jan-Hendrik Bastek, Dennis M. Kochmann:
Inverse design of nonlinear mechanical metamaterials via video denoising diffusion models. 1466-1475 - Bo Qiang, Yiran Zhou, Yuheng Ding, Ningfeng Liu, Song Song, Liangren Zhang, Bo Huang, Zhenming Liu:
Bridging the gap between chemical reaction pretraining and conditional molecule generation with a unified model. 1476-1485 - Yueqi Xie, Jingwei Yi, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, Fangzhao Wu:
Defending ChatGPT against jailbreak attack via self-reminders. 1486-1496 - R. Pacelli, S. Ariosto, Mauro Pastore, Francesco Ginelli, Marco Gherardi, Pietro Rotondo:
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit. 1497-1507 - Thomas Burri:
A challenge for the law and artificial intelligence. 1508-1509
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