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ORCIDNature Machine Intelligence, Volume 4
Volume 4, Number 1, January 2022
- The rise and fall (and rise) of datasets. 1-2
- María Amparo Grau Ruiz
, Fiachra O'Brolcháin:
Environmental robotics for a sustainable future in circular economies. 3-4 - Cameron Buckner, Risto Miikkulainen, Stephanie Forrest, Silvia Milano, James Zou, Carina Prunk, Christopher Irrgang, I. Glenn Cohen, Hao Su, Robin R. Murphy, Russell H. Taylor, Axel Krieger, Mirko Kovac, Jathan Sadowski, Vidushi Marda:
AI reflections in 2021. 5-10 - Manfred Eppe, Christian Gumbsch, Matthias Kerzel, Phuong D. H. Nguyen, Martin V. Butz, Stefan Wermter:
Intelligent problem-solving as integrated hierarchical reinforcement learning. 11-20 - Samuel C. Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das:
Optimizing molecules using efficient queries from property evaluations. 21-31 - Hong-Yu Zhou, Xiaoyu Chen, Yinghao Zhang, Ruibang Luo, Liansheng Wang, Yizhou Yu:
Generalized radiograph representation learning via cross-supervision between images and free-text radiology reports. 32-40 - Johannes Linder, Alyssa La Fleur, Zibo Chen, Ajasja Ljubetic, David Baker, Sreeram Kannan, Georg Seelig:
Interpreting neural networks for biological sequences by learning stochastic masks. 41-54 - Andres Diaz-Pinto, Nishant Ravikumar, Rahman Attar, Avan Suinesiaputra, Yitian Zhao, Eylem Levelt, Erica Dall' Armellina, Marco Lorenzi, Qingyu Chen, Tiarnan D. L. Keenan, Elvira Agrón, Emily Y. Chew, Zhiyong Lu, Chris P. Gale, Richard P. Gale, Sven Plein, Alejandro F. Frangi:
Predicting myocardial infarction through retinal scans and minimal personal information. 55-61 - Artur Luczak, Bruce L. McNaughton, Yoshimasa Kubo:
Neurons learn by predicting future activity. 62-72 - Zi Wang, Yichi Xu, Dali Wang, Jiawei Yang, Zhirong Bao:
Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement. 73-83 - Haitao Yang, Jiali Li, Kai Zhuo Lim, Chuanji Pan, Tien Van Truong, Qian Wang, Kerui Li, Shuo Li, Xiao Xiao, Meng Ding, Tianle Chen, Xiaoli Liu, Qian Xie, Pablo Valdivia y Alvarado, Xiaonan Wang, Po-Yen Chen:
Automatic strain sensor design via active learning and data augmentation for soft machines. 84-94
Volume 4, Number 2, February 2022
- Safe driving cars. 95-96
- Brandon D. Gallas, Aldo Badano, Sarah Dudgeon, Katherine Elfer, Victor Garcia, Jochen K. Lennerz, Kyle J. Myers, Nicholas Petrick, Ed Margerrison:
FDA fosters innovative approaches in research, resources and collaboration. 97-98 - Carina Prunkl:
Human autonomy in the age of artificial intelligence. 99-101 - David A. Winkler:
Potent antimalarial drugs with validated activities. 102-103 - Asaf Tzachor, Medha Devare, Brian King, Shahar Avin, Seán Ó hÉigeartaigh:
Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities. 104-109 - Peng Cui, Susan Athey:
Stable learning establishes some common ground between causal inference and machine learning. 110-115 - Xiaoyang Chen, Shengquan Chen, Shuang Song, Zijing Gao, Lin Hou, Xuegong Zhang, Hairong Lv, Rui Jiang:
Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding. 116-126 - Xiaomin Fang, Lihang Liu, Jieqiong Lei, Donglong He, Shanzhuo Zhang, Jingbo Zhou, Fan Wang, Hua Wu, Haifeng Wang:
Geometry-enhanced molecular representation learning for property prediction. 127-134 - Huanbo Sun, Katherine J. Kuchenbecker, Georg Martius:
A soft thumb-sized vision-based sensor with accurate all-round force perception. 135-145 - Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix:
When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations. 146-153 - Ekaterina Govorkova, Ema Puljak, Thea Aarrestad, Thomas James, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Nicolò Ghielmetti, Maksymilian Graczyk, Sioni Summers, Jennifer Ngadiuba, Thong Q. Nguyen, Javier M. Duarte, Zhenbin Wu:
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. 154-161 - Wolfgang Kopp, Altuna Akalin, Uwe Ohler:
Simultaneous dimensionality reduction and integration for single-cell ATAC-seq data using deep learning. 162-168 - Mathias Thor, Poramate Manoonpong:
Versatile modular neural locomotion control with fast learning. 169-179 - William J. Godinez, Eric J. Ma, Alexander T. Chao, Luying Pei, Peter Skewes-Cox, Stephen M. Canham, Jeremy L. Jenkins, Joseph M. Young, Eric J. Martin, Armand Guiguemde:
Design of potent antimalarials with generative chemistry. 180-186
Volume 4, Number 3, March 2022
- The graph connection. 187-188
- Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, Sean Ekins:
Dual use of artificial-intelligence-powered drug discovery. 189-191 - Mostafa Haghir Chehreghani:
Half a decade of graph convolutional networks. 192-193 - James T. Glazar, Vivek Shenoy:
Data-driven design of soft sensors. 194-195 - Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh C. Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Reddy Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann:
Biological underpinnings for lifelong learning machines. 196-210 - Mohit Pandey, Michael Fernández, Francesco Gentile, Olexandr Isayev, Alexander Tropsha, Abraham C. Stern, Artem Cherkasov:
The transformational role of GPU computing and deep learning in drug discovery. 211-221 - Chenyang Hong, Qin Cao, Zhenghao Zhang, Stephen Kwok-Wing Tsui, Kevin Y. Yip:
Reusability report: Capturing properties of biological objects and their relationships using graph neural networks. 222-226 - Serbülent Ünsal, Heval Atas, Muammer Albayrak, Kemal Turhan, Aybar C. Acar, Tunca Dogan:
Learning functional properties of proteins with language models. 227-245 - Jiawei Xue, Nan Jiang, Senwei Liang, Qiyuan Pang, Takahiro Yabe, Satish V. Ukkusuri, Jianzhu Ma:
Quantifying the spatial homogeneity of urban road networks via graph neural networks. 246-257 - Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf, Kristian Kersting:
Large pre-trained language models contain human-like biases of what is right and wrong to do. 258-268 - Yu-Qin Chen, Yu Chen, Chee-Kong Lee, Shengyu Zhang, Chang-Yu Hsieh:
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks. 269-278 - Yuyang Wang, Jianren Wang, Zhonglin Cao, Amir Barati Farimani:
Molecular contrastive learning of representations via graph neural networks. 279-287 - Hongyang Li, Yuanfang Guan:
Asymmetric predictive relationships across histone modifications. 288-299 - Yanyi Chu, Yan Zhang, Qiankun Wang, Lingfeng Zhang, Xuhong Wang, Yanjing Wang, Dennis Russell Salahub, Qin Xu, Jianmin Wang, Xue Jiang, Yi Xiong, Dong-Qing Wei:
A transformer-based model to predict peptide-HLA class I binding and optimize mutated peptides for vaccine design. 300-311 - Haitao Yang, Jiali Li, Kai Zhuo Lim, Chuanji Pan, Tien Van Truong, Qian Wang, Kerui Li, Shuo Li, Xiao Xiao, Meng Ding, Tianle Chen, Xiaoli Liu, Qian Xie, Pablo Valdivia y Alvarado, Xiaonan Wang, Po-Yen Chen:
Author Correction: Automatic strain sensor design via active learning and data augmentation for soft machines. 312
Volume 4, Number 4, April 2022
- Tackling the perils of dual use in AI. 313
- Sadasivan Shankar, Richard N. Zare:
The perils of machine learning in designing new chemicals and materials. 314-315 - Viknesh Sounderajah, Melissa D. McCradden, Xiaoxuan Liu, Sherri Rose, Hutan Ashrafian, Gary S. Collins, James A. Anderson, Patrick M. Bossuyt, David Moher, Ara Darzi:
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. 316-317 - Mayank Kejriwal, Henrique Santos, Alice M. Mulvehill, Deborah L. McGuinness:
Designing a strong test for measuring true common-sense reasoning. 318-322 - Travis Greene, David Martens, Galit Shmueli:
Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms. 323-330 - Markus Marks, Qiuhan Jin, Oliver Sturman, Lukas von Ziegler, Sepp Kollmorgen, Wolfger von der Behrens, Valerio Mante, Johannes Bohacek, Mehmet Fatih Yanik:
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments. 331-340 - Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan, Hiroshi Funakubo, Maxim A. Ziatdinov, Sergei V. Kalinin:
Experimental discovery of structure-property relationships in ferroelectric materials via active learning. 341-350 - Thomas D. Barrett, Aleksei O. Malyshev, A. I. Lvovsky:
Autoregressive neural-network wavefunctions for ab initio quantum chemistry. 351-358 - Pantelis-Rafail Vlachas, Georgios Arampatzis, Caroline Uhler, Petros Koumoutsakos:
Multiscale simulations of complex systems by learning their effective dynamics. 359-366 - Martin J. A. Schuetz, John Kyle Brubaker, Helmut G. Katzgraber:
Combinatorial optimization with physics-inspired graph neural networks. 367-377 - Tom Altenburg, Sven H. Giese, Shengbo Wang, Thilo Muth, Bernhard Y. Renard:
Ad hoc learning of peptide fragmentation from mass spectra enables an interpretable detection of phosphorylated and cross-linked peptides. 378-388 - Hao Li, Yu Sun, Hao Hong, Xin Huang, Huan Tao, Qiya Huang, Longteng Wang, Kang Xu, Jingbo Gan, Hebing Chen, Xiaochen Bo:
Inferring transcription factor regulatory networks from single-cell ATAC-seq data based on graph neural networks. 389-400 - Parmida Ghahremani, Yanyun Li, Arie E. Kaufman, Rami Vanguri, Noah Greenwald, Michael Angelo, Travis J. Hollmann, Saad Nadeem:
Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification. 401-412 - Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia:
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. 413 - Ekaterina Govorkova, Ema Puljak, Thea Aarrestad, Thomas James, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Nicolò Ghielmetti, Maksymilian Graczyk, Sioni Summers, Jennifer Ngadiuba, Thong Q. Nguyen, Javier M. Duarte, Zhenbin Wu:
Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. 414
Volume 4, Number 5, May 2022
- A soft touch for robots. 415
- Luís A. Nunes Amaral:
A cautionary tale from the machine scientist. 416-417 - Nils C. Köbis, Christopher Starke, Iyad Rahwan:
The promise and perils of using artificial intelligence to fight corruption. 418-424 - Luca Massari, Giulia Fransvea, Jessica D'Abbraccio, Mariangela Filosa, Giuseppe Terruso, Andrea Aliperta, Giacomo D'Alesio, Martina Zaltieri, Emiliano Schena, Eduardo Palermo, Edoardo Sinibaldi, Calogero Maria Oddo:
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin. 425-435 - Jiqing Wu, Nanda Horeweg, Marco de Bruyn, Remi A. Nout, Ina M. Jürgenliemk-Schulz, Ludy C. H. W. Lutgens, Jan J. Jobsen, Elzbieta M. van der Steen-Banasik, Hans W. Nijman, Vincent T. H. B. M. Smit, Tjalling Bosse, Carien L. Creutzberg, Viktor H. Koelzer:
Automated causal inference in application to randomized controlled clinical trials. 436-444 - Alexander V. Belikov, Andrey Rzhetsky, James A. Evans:
Prediction of robust scientific facts from literature. 445-454 - Anthony Bilodeau, Constantin V. L. Delmas, Martin Parent, Paul De Koninck, Audrey Durand, Flavie Lavoie-Cardinal:
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations. 455-466 - Arjun Rao, Philipp Plank, Andreas Wild, Wolfgang Maass:
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware. 467-479 - Lidong Yang, Jialin Jiang, Xiaojie Gao, Qinglong Wang, Qi Dou, Li Zhang:
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning. 480-493 - Longxi Zhou, Xianglin Meng, Yuxin Huang, Kai Kang, Juexiao Zhou, Yuetan Chu, Haoyang Li, Dexuan Xie, Jiannan Zhang, Weizhen Yang, Na Bai, Yi Zhao, Mingyan Zhao, Guohua Wang, Lawrence Carin, Xigang Xiao, Kaijiang Yu, Zhaowen Qiu, Xin Gao:
An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors. 494-503
Volume 4, Number 6, June 2022
- Privacy debate obscures pandemic power shifts. 505
- Marc-Michael Blum:
No chemical killer AI (yet). 506-507 - Jakob Mökander, Luciano Floridi:
From algorithmic accountability to digital governance. 508-509 - Lorijn Zaadnoordijk, Tarek R. Besold, Rhodri Cusack:
Lessons from infant learning for unsupervised machine learning. 510-520 - Noelia Ferruz, Birte Höcker:
Controllable protein design with language models. 521-532 - Keng Peng Tee, Samuel Cheong, Jun Li, Gowrishankar Ganesh:
A framework for tool cognition in robots without prior tool learning or observation. 533-543 - Daniel Flam-Shepherd, Tony C. Wu, Xuemei Gu, Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Learning interpretable representations of entanglement in quantum optics experiments using deep generative models. 544-554 - Jeff Guo, Vendy Fialková, Juan Diego Arango, Christian Margreitter, Jon Paul Janet, Kostas Papadopoulos, Ola Engkvist, Atanas Patronov:
Improving de novo molecular design with curriculum learning. 555-563 - Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. 564-573 - Anna-Maria Georgarakis, Michele Xiloyannis, Peter Wolf, Robert Riener:
A textile exomuscle that assists the shoulder during functional movements for everyday life. 574-582 - Daniel R. Wong, Jay Conrad, Noah R. Johnson, Jacob Ayers, Annelies Laeremans, Joanne C. Lee, Jisoo Lee, Stanley B. Prusiner, Sourav Bandyopadhyay, Atul J. Butte, Nick A. Paras, Michael J. Keiser:
Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics. 583-595 - Ze Zhang, Woo Yong Chang, Kaiwen Wang, Yuqiu Yang, Xinlei Wang, Chen Yao, Tuoqi Wu, Li Wang, Tao Wang:
Interpreting the B-cell receptor repertoire with single-cell gene expression using Benisse. 596-604
Volume 4, Number 7, July 2022
- AI podcasts for the summer. 605-606
- Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, Sean Ekins:
A teachable moment for dual-use. 607 - Emmie Hine, Luciano Floridi:
New deepfake regulations in China are a tool for social stability, but at what cost? 608-610 - Stefan Feuerriegel, Yash Raj Shrestha, Georg von Krogh, Ce Zhang:
Bringing artificial intelligence to business management. 611-613 - William Poole:
In vitro convolutional neural networks. 614-615 - Florian Heigwer:
Learning the missing channel. 616-617 - Elizabeth R. Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy, Juan Carrasquilla, Pooya Ronagh:
Neural Error Mitigation of Near-Term Quantum Simulations. 618-624 - Xiewei Xiong, Tong Zhu, Yun Zhu, Mengyao Cao, Jin Xiao, Li Li, Fei Wang, Chunhai Fan, Hao Pei:
Molecular convolutional neural networks with DNA regulatory circuits. 625-635 - Christopher J. Soelistyo, Giulia Vallardi, Guillaume Charras, Alan R. Lowe:
Learning biophysical determinants of cell fate with deep neural networks. 636-644 - Yuquan Li, Chang-Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan, Qifeng Bai, Huanxiang Liu, Shengyu Zhang, Xiaojun Yao:
An adaptive graph learning method for automated molecular interactions and properties predictions. 645-651 - Felix Ruppert, Alexander Badri-Spröwitz:
Learning plastic matching of robot dynamics in closed-loop central pattern generators. 652-660
Volume 4, Number 8, August 2022
- Achieving net zero emissions with machine learning: the challenge ahead. 661-662
- Gerhard Gompper:
Delivering microcargo with artificial microtubules. 663-664 - Ahmed M. Alaa:
Mining for informative signals in biological sequences. 665-666 - Yang Cao, Cher Tian Ser, Marta Skreta, Kjell Jorner, Nathanael Kusanda, Alán Aspuru-Guzik:
Reinforcement learning supercharges redox flow batteries. 667-668 - Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Advances, challenges and opportunities in creating data for trustworthy AI. 669-677 - Hongri Gu, Emre Hanedan, Quentin Boehler, Tian-Yun Huang, Arnold J. T. M. Mathijssen, Bradley J. Nelson:
Artificial microtubules for rapid and collective transport of magnetic microcargoes. 678-684 - Cosmin I. Bercea, Benedikt Wiestler, Daniel Rueckert, Shadi Albarqouni:
Federated disentangled representation learning for unsupervised brain anomaly detection. 685-695 - Meng Yang, Yueyuxiao Yang, Chenxi Xie, Ming Ni, Jian Liu, Huanming Yang, Feng Mu, Jian Wang:
Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale. 696-709 - Subham Choudhury, Michael Moret, Pierre Salvy, Daniel Weilandt, Vassily Hatzimanikatis, Ljubisa Miskovic:
Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks. 710-719 - Shree Sowndarya S. V., Jeffrey N. Law, Charles Edison Tripp, Dmitry Duplyakin, Erotokritos Skordilis, David Biagioni, Robert S. Paton, Peter C. St. John:
Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries. 720-730 - Jeff Guo, Vendy Fialková, Juan Diego Arango, Christian Margreitter, Jon Paul Janet, Kostas Papadopoulos, Ola Engkvist, Atanas Patronov:
Author Correction: Improving de novo molecular design with curriculum learning. 731
Volume 4, Number 9, September 2022
- Collaborative creativity in AI. 733
- Zoë Porter, Annette Zimmermann, Phillip Morgan, John A. McDermid, Tom Lawton, Ibrahim Habli:
Distinguishing two features of accountability for AI technologies. 734-736 - Francisco J. Valero Cuevas, Andrew Erwin:
Bio-robots step towards brain-body co-adaptation. 737-738 - Shuangjia Zheng, Youhai Tan, Zhenyu Wang, Chengtao Li, Zhiqing Zhang, Xu Sang, Hongming Chen, Yuedong Yang:
Accelerated rational PROTAC design via deep learning and molecular simulations. 739-748 - Yasin Almalioglu, Mehmet Turan, Niki Trigoni, Andrew Markham:
Deep learning-based robust positioning for all-weather autonomous driving. 749-760 - Peyman Hosseinzadeh Kassani, Fred Lu, Yann Le Guen, Michaël E. Belloy, Zihuai He:
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants. 761-771 - Shuan Chen, Yousung Jung:
A generalized-template-based graph neural network for accurate organic reactivity prediction. 772-780 - Renhao Liu, Yu Sun, Jiabei Zhu, Lei Tian, Ulugbek S. Kamilov:
Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields. 781-791 - Alicja Gosiewska, Katarzyna Woznica, Przemyslaw Biecek:
Interpretable meta-score for model performance. 792-800
Volume 4, Number 10, October 2022
- Revisiting code reusability. 801
- Fei Yang, Yu Yao:
A new regulatory framework for algorithm-powered recommendation services in China. 802-803 - Henrik Skaug Sætra, Harald Borgebund, Mark Coeckelbergh:
Avoid diluting democracy by algorithms. 804-806 - Batia Mishan Wiesenfeld, Yin Aphinyanaphongs, Oded Nov:
AI model transferability in healthcare: a sociotechnical perspective. 807-809 - Matteo M. Wauters, Evert P. L. van Nieuwenburg:
Reusability report: Comparing gradient descent and Monte Carlo tree search optimization of quantum annealing schedules. 810-813 - Thomas Ward, Alexander Johnsen, Stanley Ng, François Chollet:
Forecasting SARS-CoV-2 transmission and clinical risk at small spatial scales by the application of machine learning architectures to syndromic surveillance data. 814-827 - Philipp Hess, Markus Drüke, Stefan Petri, Felix M. Strnad, Niklas Boers:
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models. 828-839 - Egbert Castro, Abhinav Godavarthi, Julian Rubinfien, Kevin B. Givechian, Dhananjay Bhaskar, Smita Krishnaswamy:
Transformer-based protein generation with regularized latent space optimization. 840-851 - Fan Yang, Wenchuan Wang, Fang Wang, Yuan Fang, Duyu Tang, Junzhou Huang, Hui Lu, Jianhua Yao:
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data. 852-866 - Adriel Saporta, Xiaotong Gui, Ashwin Agrawal, Anuj Pareek, Steven Q. H. Truong, Chanh D. T. Nguyen, Van Doan Ngo, Jayne Seekins, Francis G. Blankenberg, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar:
Benchmarking saliency methods for chest X-ray interpretation. 867-878 - Di He, Qiao Liu, You Wu, Lei Xie:
A context-aware deconfounding autoencoder for robust prediction of personalized clinical drug response from cell-line compound screening. 879-892 - Kuanming Yao, Jingkun Zhou, Qingyun Huang, Mengge Wu, Chun Ki Yiu, Jian Li, Xingcan Huang, Dengfeng Li, Jingyou Su, Senlin Hou, Yiming Liu, Ya Huang, Ziyan Tian, Jiyu Li, Hu Li, Rui Shi, Binbin Zhang, Jingyi Zhu, Tsz Hung Wong, Huiling Jia, Zhan Gao, Yuyu Gao, Yu Zhou, Wooyoung Park, Enming Song, Mengdi Han, Haixia Zhang, Junsheng Yu, Lidai Wang, Wen Jung Li, Xinge Yu:
Encoding of tactile information in hand via skin-integrated wireless haptic interface. 893-903 - Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. 904
Volume 4, Number 11, November 2022
- Data sovereignty in genomics and medical research. 905-906
- Lorenzo Jamone:
Modelling human tool use in robots. 907-908 - Nima Boscarino, Reed A. Cartwright, Keolu Fox, Krystal S. Tsosie:
Federated learning and Indigenous genomic data sovereignty. 909-911 - William J. Bolton, Cosmin Badea, Pantelis Georgiou, Alison H. Holmes, Timothy M. Rawson:
Developing moral AI to support decision-making about antimicrobial use. 912-915 - Diana Mincu, Subhrajit Roy:
Developing robust benchmarks for driving forward AI innovation in healthcare. 916-921 - Ge Wang, Andreu Badal, Xun Jia, Jonathan S. Maltz, Klaus Mueller, Kyle J. Myers, Chuang Niu, Michael W. Vannier, Pingkun Yan, Zhou Yu, Rongping Zeng:
Development of metaverse for intelligent healthcare. 922-929 - Pingchuan Ma, Stavros Petridis, Maja Pantic:
Visual speech recognition for multiple languages in the wild. 930-939 - Justin Lakkis, Amelia Schroeder, Kenong Su, Michelle Y. Y. Lee, Alexander C. Bashore, Muredach P. Reilly, Mingyao Li:
A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputation. 940-952 - Jason Lequyer, Reuben Philip, Amit Sharma, Wen-Hsin Hsu, Laurence Pelletier:
A fast blind zero-shot denoiser. 953-963 - Jie Zhang, Yishan Du, Pengfei Zhou, Jinru Ding, Shuai Xia, Qian Wang, Feiyang Chen, Mu Zhou, Xuemei Zhang, Weifeng Wang, Hongyan Wu, Lu Lu, Shaoting Zhang:
Predicting unseen antibodies' neutralizability via adaptive graph neural networks. 964-976 - Arsam Aryandoust, Anthony Patt, Stefan Pfenninger:
Enhanced spatio-temporal electric load forecasts using less data with active deep learning. 977-991 - Ramin M. Hasani, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, Daniela Rus:
Closed-form continuous-time neural networks. 992-1003 - Xiangxiang Zeng, Hongxin Xiang, Linhui Yu, Jianmin Wang, Kenli Li, Ruth Nussinov, Feixiong Cheng:
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework. 1004-1016 - Haicang Zhang, Michelle S. Xu, Xiao Fan, Wendy K. Chung, Yufeng Shen:
Predicting functional effect of missense variants using graph attention neural networks. 1017-1028 - Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Sven Nebelung, Daniel Truhn:
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. 1029-1039 - Chen Zhou, Ming-Cheng Miao, Xin-Ran Chen, Yi-Fei Hu, Qi Chang, Ming-Yuan Yan, Shu-Guang Kuai:
Human-behaviour-based social locomotion model improves the humanization of social robots. 1040-1052 - Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. 1053 - Shuan Chen, Yousung Jung:
Author Correction: A generalized-template-based graph neural network for accurate organic reactivity prediction. 1054
Volume 4, Number 12, December 2022
- Much to discuss in AI ethics. 1055-1056
- Alexandra George, Toby Walsh:
Can AI invent? 1057-1060 - Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Advancing ethics review practices in AI research. 1061-1064 - Kohitij Kar, Simon Kornblith, Evelina Fedorenko:
Interpretability of artificial neural network models in artificial intelligence versus neuroscience. 1065-1067 - Cédric Colas, Tristan Karch, Clément Moulin-Frier, Pierre-Yves Oudeyer:
Language and culture internalization for human-like autotelic AI. 1068-1076 - Hao Ju, Rongshun Juan, Randy Gomez, Keisuke Nakamura, Guangliang Li:
Transferring policy of deep reinforcement learning from simulation to reality for robotics. 1077-1087 - Shushan Toneyan, Ziqi Tang, Peter K. Koo:
Evaluating deep learning for predicting epigenomic profiles. 1088-1100 - Maxim A. Ziatdinov, Ayana Ghosh, Chun Yin Wong, Sergei V. Kalinin:
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy. 1101-1112 - Daniel Floryan, Michael D. Graham:
Data-driven discovery of intrinsic dynamics. 1113-1120 - Jie Cao, Xiaosong Zhang, Vahakn Shahinian, Huiying Yin, Diane Steffick, Rajiv Saran, Susan Crowley, Michael Mathis, Girish N. Nadkarni, Michael Heung, Karandeep Singh:
Generalizability of an acute kidney injury prediction model across health systems. 1121-1129 - Lucian Chan, Rajendra Kumar, Marcel L. Verdonk, Carl Poelking:
A multilevel generative framework with hierarchical self-contrasting for bias control and transparency in structure-based ligand design. 1130-1142 - Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos J. Storkey, Miguel O. Bernabeu:
Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning. 1143-1154 - Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis:
Deep transfer operator learning for partial differential equations under conditional shift. 1155-1164 - Alejandro Güemes, Carlos Sanmiguel Vila, Stefano Discetti:
Super-resolution generative adversarial networks of randomly-seeded fields. 1165-1173 - Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins, Do Soon Kim, Bojan Tunguz, Walter Reade, Maggie Demkin, Jonathan Romano, Roger Wellington-Oguri, John J. Nicol, Jiayang Gao, Kazuki Onodera, Kazuki Fujikawa, Hanfei Mao, Gilles Vandewiele, Michele Tinti, Bram Steenwinckel, Takuya Ito, Taiga Noumi, Shujun He, Keiichiro Ishi, Youhan Lee, Fatih Öztürk, King Yuen Chiu, Emin Öztürk, Karim Amer, Mohamed Fares, Rhiju Das:
Deep learning models for predicting RNA degradation via dual crowdsourcing. 1174-1184 - Gido M. van de Ven, Tinne Tuytelaars, Andreas S. Tolias:
Three types of incremental learning. 1185-1197 - Yongbin Jin, Xianwei Liu, Yecheng Shao, Hongtao Wang, Wei Yang:
High-speed quadrupedal locomotion by imitation-relaxation reinforcement learning. 1198-1208 - Yiyuan Fang, Shuyi Deng, Cai Li:
A generalizable deep learning framework for inferring fine-scale germline mutation rate maps. 1209-1223 - Eric Bach, Emma Schymanski, Juho Rousu:
Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data. 1224-1237 - Jakub Kudela:
A critical problem in benchmarking and analysis of evolutionary computation methods. 1238-1245 - Tiago Janela, Jürgen Bajorath:
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models. 1246-1255 - Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das:
Large-scale chemical language representations capture molecular structure and properties. 1256-1264 - Zhenge Jia, Xiaowei Xu, Jingtong Hu, Yiyu Shi:
Low-power object-detection challenge on unmanned aerial vehicles. 1265-1266 - Ramin M. Hasani, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, Daniela Rus:
Publisher Correction: Closed-form continuous-time neural networks. 1267
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