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ORCIDNature Machine Intelligence, Volume 6
Volume 6, Number 1, 2024
- Is it five already? 1
- Andreas Kleppe
, Ole-Johan Skrede, Knut Liestøl, David J. Kerr, Håvard E. Danielsen:
Guidelines for study protocols describing predefined validations of prediction models in medical deep learning and beyond. 2-3 - Étienne Ollion, Rubing Shen, Ana Macanovic, Arnault Chatelain:
The dangers of using proprietary LLMs for research. 4-5 - Noelia Ferruz, Marinka Zitnik, Pierre-Yves Oudeyer, Emmie Hine, Nandana Sengupta, Yiyu Shi, Diana Mincu, Sebastian Porsdam Mann, Payel Das, Francesco Stella:
Anniversary AI reflections. 6-12 - Séverine Atis, Lionel Agostini:
Catching up with missing particles. 13-14 - Milena Pavlovic, Ghadi S. Al Hajj, Chakravarthi Kanduri, Johan Pensar, Mollie Wood, Ludvig Magne Sollid, Victor Greiff, Geir Kjetil Sandve:
Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics. 15-24 - Yutong Sha, Yuchi Qiu, Peijie Zhou, Qing Nie:
Reconstructing growth and dynamic trajectories from single-cell transcriptomics data. 25-39 - Simone Ciceri, Lorenzo Cassani, Matteo Osella, Pietro Rotondo, Filippo Valle, Marco Gherardi:
Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalization. 40-47 - Yaning Han, Ke Chen, Yunke Wang, Wenhao Liu, Zhouwei Wang, Xiaojing Wang, Chuanliang Han, Jiahui Liao, Kang Huang, Shengyuan Cai, Yiting Huang, Nan Wang, Jinxiu Li, Yangwangzi Song, Jing Li, Guo-Dong Wang, Liping Wang, Yaping Zhang, Pengfei Wei:
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework. 48-61 - Wei Feng, Lvwei Wang, Zaiyun Lin, Yanhao Zhu, Han Wang, Jianqiang Dong, Rong Bai, Huting Wang, Jielong Zhou, Wei Peng, Bo Huang, Wenbiao Zhou:
Generation of 3D molecules in pockets via a language model. 62-73 - Aubin Ramon, Montader Ali, Misha Atkinson, Alessio Saturnino, Kieran Didi, Cristina Visentin, Stefano Ricagno, Xing Xu, Matthew Greenig, Pietro Sormanni:
Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV. 74-91 - Sarmad Ahmad Abbasi, Awais Ahmed, Seungmin Noh, Nader Latifi Gharamaleki, Seonhyoung Kim, A. M. Masum Bulbul Chowdhury, Jin-young Kim, Salvador Pané, Bradley J. Nelson, Hongsoo Choi:
Autonomous 3D positional control of a magnetic microrobot using reinforcement learning. 92-105 - Arvin Tashakori, Zenan Jiang, Amir Servati, Saeid Soltanian, Harishkumar Narayana, Katherine Le, Caroline Nakayama, Chieh-ling Yang, Z. Jane Wang, Janice J. Eng, Peyman Servati:
Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves. 106-118 - Yutong Sha, Yuchi Qiu, Peijie Zhou, Qing Nie:
Publisher Correction: Reconstructing growth and dynamic trajectories from single-cell transcriptomics data. 119
Volume 6, Number 2, 2024
- AI protein shake-up. 121
- Katja Seeliger, Martin N. Hebart:
What comparing deep neural networks can teach us about human vision. 122-123 - Stephan Allenspach, Jan A. Hiss, Gisbert Schneider:
Neural multi-task learning in drug design. 124-137 - Suyue Lyu, Shahin Sowlati-Hashjin, Michael Garton:
Variational autoencoder for design of synthetic viral vector serotypes. 147-160 - Kevin Maik Jablonka, Philippe Schwaller, Andres Ortega-Guerrero, Berend Smit:
Leveraging large language models for predictive chemistry. 161-169 - Carlos Outeiral, Charlotte M. Deane:
Codon language embeddings provide strong signals for use in protein engineering. 170-179 - Jens Oppliger, Michael M. Denner, Julia Küspert, Ruggero Frison, Qisi Wang, Alexander Morawietz, Oleh Ivashko, Ann-Christin Dippel, Martin von Zimmermann, Izabela Bialo, Leonardo Martinelli, Benoît Fauqué, Jaewon Choi, Mirian Garcia-Fernandez, Ke-Jin Zhou, Niels Bech Christensen, Tohru Kurosawa, Naoki Momono, Migaku Oda, Fabian D. Natterer, Mark H. Fischer, Titus Neupert, Johan Chang:
Weak signal extraction enabled by deep neural network denoising of diffraction data. 180-186 - Benjamin Q. Huynh, Elizabeth T. Chin, Allison Koenecke, Derek Ouyang, Daniel E. Ho, Mathew V. Kiang, David H. Rehkopf:
Mitigating allocative tradeoffs and harms in an environmental justice data tool. 187-194 - Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
State-specific protein-ligand complex structure prediction with a multiscale deep generative model. 195-208 - Maxat Kulmanov, Francisco J. Guzmán-Vega, Paula Duek Roggli, Lydie Lane, Stefan T. Arold, Robert Hoehndorf:
Protein function prediction as approximate semantic entailment. 220-228 - Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes:
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. 229-242 - Kenny Schlegel, Denis Kleyko, Benjamin H. Brinkmann, Ewan S. Nurse, Ross W. Gayler, Peer Neubert:
Lessons from a challenge on forecasting epileptic seizures from non-cerebral signals. 243-244
Volume 6, Number 3, 2024
- The new NeuroAI. 245
- Eva Erman, Markus Furendal:
The democratization of global AI governance and the role of tech companies. 246-248 - Glen M. Hocky:
Connecting molecular properties with plain language. 249-250 - Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri:
A collective AI via lifelong learning and sharing at the edge. 251-264 - A. Emin Orhan, Brenden M. Lake:
Learning high-level visual representations from a child's perspective without strong inductive biases. 271-283 - Yuhe Zhang, Tobias Ritschel, Pablo Villanueva-Perez:
Reusability report: Unpaired deep-learning approaches for holographic image reconstruction. 284-290 - Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar, Yan Xia, Bernard D. Keavney, Sven Plein, Tanveer F. Syeda-Mahmood, Alejandro F. Frangi:
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology. 291-306 - Yingying Cao, Tian-Gen Chang, Sahil Sahni, Eytan Ruppin:
Reusability report: Leveraging supervised learning to uncover phenotype-relevant biology from single-cell RNA sequencing data. 307-314 - Tian Lan, Shuquan Su, Pengyao Ping, Gyorgy Hutvagner, Tao Liu, Yi Pan, Jinyan Li:
Generating mutants of monotone affinity towards stronger protein complexes through adversarial learning. 315-325 - Yuanyuan Jiang, Guo Zhang, Jing You, Hailin Zhang, Rui Yao, Huan-Zhang Xie, Liyun Zhang, Ziyi Xia, Mengzhe Dai, Yunjie Wu, Linli Li, Sheng-Yong Yang:
PocketFlow is a data-and-knowledge-driven structure-based molecular generative model. 326-337 - Kyle Swanson, Gary Liu, Denise B. Catacutan, Autumn Arnold, James Zou, Jonathan M. Stokes:
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics. 338-353 - Jacopo Tagliabue, Federico Bianchi, Tobias Schnabel, Giuseppe Attanasio, Ciro Greco, Gabriel de Souza P. Moreira, Patrick John Chia:
Author Correction: A challenge for rounded evaluation of recommender systems. 368
Volume 6, Number 4, 2024
- The rewards of reusable machine learning code. 369
- Marieke A. R. Bak, Vince I. Madai, Leo Anthony Celi, Georgios Kaissis, Ronald Cornet, Menno Maris, Daniel Rueckert, Alena Buyx, Stuart McLennan:
Federated learning is not a cure-all for data ethics. 370-372 - Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb:
The curious case of the test set AUROC. 373-376 - Mike H. M. Teodorescu, Mingang K. Geiger, Lily Morse:
Dangers of speech technology for workplace diversity. 377-380 - Justin N. Wood:
Artificial intelligence tackles the nature-nurture debate. 381-382 - Hannah Rose Kirk, Bertie Vidgen, Paul Röttger, Scott A. Hale:
The benefits, risks and bounds of personalizing the alignment of large language models to individuals. 383-392 - Tianyi Li, Luca Biferale, Fabio Bonaccorso, Martino Andrea Scarpolini, Michele Buzzicotti:
Synthetic Lagrangian turbulence by generative diffusion models. 393-403 - Adamo Young, Hannes L. Röst, Bo Wang:
Tandem mass spectrum prediction for small molecules using graph transformers. 404-416 - Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-conditional diffusion model for molecular linker design. 417-427 - Taoyong Cui, Chenyu Tang, Mao Su, Shufei Zhang, Yuqiang Li, Lei Bai, Yuhan Dong, Xingao Gong, Wanli Ouyang:
Geometry-enhanced pretraining on interatomic potentials. 428-436 - Michael A. Skinnider:
Invalid SMILES are beneficial rather than detrimental to chemical language models. 437-448 - Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, Mengdi Wang:
A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions. 449-460 - Tao Xu, Haoyuan Shi, Wanling Gao, Xiaosong Wang, Zhenyu Yue:
Reusability report: Uncovering associations in biomedical bipartite networks via a bilinear attention network with domain adaptation. 461-466 - Xupeng Chen, Ran Wang, Amirhossein Khalilian-Gourtani, Leyao Yu, Patricia Dugan, Daniel Friedman, Werner K. Doyle, Orrin Devinsky, Yao Wang, Adeen Flinker:
A neural speech decoding framework leveraging deep learning and speech synthesis. 467-480 - Johannes Kühn, Tingli Hu, Alexander Toedtheide, Edmundo Pozo Fortunic, Elisabeth Rose Jensen, Sami Haddadin:
The synergy complement control approach for seamless limb-driven prostheses. 481-492 - Dylan S. Shah, Joshua P. Powers, Liana G. Tilton, Sam Kriegman, Josh C. Bongard, Rebecca Kramer-Bottiglio:
Author Correction: A soft robot that adapts to environments through shape change. 493 - Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb:
Publisher Correction: The curious case of the test set AUROC. 494
Volume 6, Number 5, 2024
- Empathic AI can't get under the skin. 495
- Garriy Shteynberg, Jodi Halpern, Amir Sadovnik, Jon Garthoff, Anat Perry, Jessica Hay, Carlos Montemayor, Michael A. Olson, Tim L. Hulsey, Abrol Fairweather:
Does it matter if empathic AI has no empathy? 496-497 - Diego Marcondes, Adilson Simonis, Junior Barrera:
Back to basics to open the black box. 498-501 - Ge Wang:
Diving into deep learning. 502-503 - Thomas A. Berrueta, Allison Pinosky, Todd D. Murphey:
Maximum diffusion reinforcement learning. 504-514 - Florian Fürrutter, Gorka Muñoz-Gil, Hans J. Briegel:
Quantum circuit synthesis with diffusion models. 515-524 - Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D. White, Philippe Schwaller:
Augmenting large language models with chemistry tools. 525-535 - Milong Ren, Chungong Yu, Dongbo Bu, Haicang Zhang:
Accurate and robust protein sequence design with CarbonDesign. 536-547 - Ning Wang, Jiang Bian, Yuchen Li, Xuhong Li, Shahid Mumtaz, Linghe Kong, Haoyi Xiong:
Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning. 548-557 - Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Predicting equilibrium distributions for molecular systems with deep learning. 558-567 - Abdourahmane Diaw, Michael M. McKerns, Irina Sagert, L. G. Stanton, Michael S. Murillo:
Efficient learning of accurate surrogates for simulations of complex systems. 568-577
Volume 6, Number 6, 2024
- Will generative AI transform robotics? 579
- Mayank Kejriwal, Eric J. Kildebeck, Robert J. Steininger, Abhinav Shrivastava:
Challenges, evaluation and opportunities for open-world learning. 580-588 - Yuanqi Du, Arian R. Jamasb, Jeff Guo, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, Tom L. Blundell:
Machine learning-aided generative molecular design. 589-604 - Lidong Yang, Jialin Jiang, Fengtong Ji, Yangmin Li, Kai-Leung Yung, Antoine Ferreira, Li Zhang:
Machine learning for micro- and nanorobots. 605-618 - Kevin Max, Laura Kriener, Garibaldi Pineda García, Thomas Nowotny, Ismael Jaras, Walter Senn, Mihai A. Petrovici:
Learning efficient backprojections across cortical hierarchies in real time. 619-630 - Qianying Cao, Somdatta Goswami, George Em Karniadakis:
Laplace neural operator for solving differential equations. 631-640 - Alpha Renner, Lazar Supic, Andreea Danielescu, Giacomo Indiveri, Bruno A. Olshausen, Yulia Sandamirskaya, Friedrich T. Sommer, Edward Paxon Frady:
Neuromorphic visual scene understanding with resonator networks. 641-652 - Alpha Renner, Lazar Supic, Andreea Danielescu, Giacomo Indiveri, Edward Paxon Frady, Friedrich T. Sommer, Yulia Sandamirskaya:
Visual odometry with neuromorphic resonator networks. 653-663 - Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang, Tina Eliassi-Rad, Farinaz Koushanfar:
Distributed constrained combinatorial optimization leveraging hypergraph neural networks. 664-672 - Huan Yee Koh, Anh T. N. Nguyen, Shirui Pan, Lauren T. May, Geoffrey I. Webb:
Physicochemical graph neural network for learning protein-ligand interaction fingerprints from sequence data. 673-687 - Duanhua Cao, Geng Chen, Jiaxin Jiang, Jie Yu, Runze Zhang, Mingan Chen, Wei Zhang, Lifan Chen, Feisheng Zhong, Yingying Zhang, Chenghao Lu, Xutong Li, Xiaomin Luo, Sulin Zhang, Mingyue Zheng:
Generic protein-ligand interaction scoring by integrating physical prior knowledge and data augmentation modelling. 688-700 - Evan Seitz, David M. McCandlish, Justin B. Kinney, Peter K. Koo:
Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models. 701-713 - Iksung Kang, Qinrong Zhang, Stella X. Yu, Na Ji:
Coordinate-based neural representations for computational adaptive optics in widefield microscopy. 714-725 - Chenguang Li, Gabriel Kreiman, Sharad Ramanathan:
Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks. 726-738
Volume 6, Number 7, 2024
- A question of trust for AI research in medicine. 739
- Robert L. Baines, Dylan S. Shah, Jeremy Marvel, Jennifer C. Case, Andrew Spielberg:
The need for reproducible research in soft robotics. 740-741 - Gaoyang Liu, Chen Wang, Tian Xia:
Shielding sensitive medical imaging data. 742-743 - Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou:
Systematic analysis of 32,111 AI model cards characterizes documentation practice in AI. 744-753 - Maria Boulougouri, Pierre Vandergheynst, Daniel Probst:
Molecular set representation learning. 754-763 - Alexander Ziller, Tamara T. Mueller, Simon Stieger, Leonhard F. Feiner, Johannes Brandt, Rickmer Braren, Daniel Rueckert, Georgios Kaissis:
Reconciling privacy and accuracy in AI for medical imaging. 764-774 - Osama Abdin, Philip M. Kim:
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion. 775-786 - Lei Han, Qingxu Zhu, Jiapeng Sheng, Chong Zhang, Tingguang Li, Yizheng Zhang, He Zhang, Yuzhen Liu, Cheng Zhou, Rui Zhao, Jie Li, Yufeng Zhang, Rui Wang, Wanchao Chi, Xiong Li, Yonghui Zhu, Lingzhu Xiang, Xiao Teng, Zhengyou Zhang:
Lifelike agility and play in quadrupedal robots using reinforcement learning and generative pre-trained models. 787-798 - Dong Chen, Jian Liu, Guo-Wei Wei:
Multiscale topology-enabled structure-to-sequence transformer for protein-ligand interaction predictions. 799-810 - Petru-Daniel Tudosiu, Walter H. L. Pinaya, Pedro Ferreira Da Costa, Jessica Dafflon, Ashay Patel, Pedro Borges, Virginia Fernandez, Mark S. Graham, Robert J. Gray, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Realistic morphology-preserving generative modelling of the brain. 811-819 - James Gornet, Matt Thomson:
Automated construction of cognitive maps with visual predictive coding. 820-833 - Yoo-Geun Ham, Yong-Sik Joo, Jeong-Hwan Kim, Jeong-Gil Lee:
Partial-convolution-implemented generative adversarial network for global oceanic data assimilation. 834-843
Volume 6, Number 8, 2024
- What is in your LLM-based framework? 845
- Silvia Milano, Sven Nyholm:
Advanced AI assistants that act on our behalf may not be ethically or legally feasible. 846-847 - Nicholas Vincent:
A step forward in tracing and documenting dataset provenance. 848-849 - Margaret C. von Ebers, Xue-Xin Wei:
Cognitive maps from predictive vision. 850-851 - Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, Tanmoy Chakraborty, Giovanni Luca Ciampaglia, David P. A. Corney, Renee DiResta, Emilio Ferrara, Scott Hale, Alon Y. Halevy, Eduard H. Hovy, Heng Ji, Filippo Menczer, Rubén Míguez, Preslav Nakov, Dietram Scheufele, Shivam Sharma, Giovanni Zagni:
Factuality challenges in the era of large language models and opportunities for fact-checking. 852-863 - Shuangxia Ren, Gregory F. Cooper, Lujia Chen, Xinghua Lu:
An interpretable deep learning framework for genome-informed precision oncology. 864-875 - Rui Jiang, Xiaoxu Yin, Pengshuai Yang, Lingchao Cheng, Juan Hu, Jiao Yang, Ying Wang, Xiaodan Fu, Li Shang, Liling Li, Wei Lin, Huan Zhou, Fufeng Chen, Xuegong Zhang, Zhongliang Hu, Hairong Lv:
A transformer-based weakly supervised computational pathology method for clinical-grade diagnosis and molecular marker discovery of gliomas. 876-891 - Yue Huang, Chengguang Zhu, Xiaokang Yang, Manhua Liu:
High-resolution real-space reconstruction of cryo-EM structures using a neural field network. 892-903 - Yang Long, Haoran Xue, Baile Zhang:
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands. 904-910 - Melissa Sanabria, Jonas Hirsch, Pierre M. Joubert, Anna R. Poetsch:
DNA language model GROVER learns sequence context in the human genome. 911-923 - Shihao Feng, Zhenyu Chen, Chengwei Zhang, Yuhao Xie, Sergey Ovchinnikov, Yi Qin Gao, Sirui Liu:
Integrated structure prediction of protein-protein docking with experimental restraints using ColabDock. 924-935 - Surbhi Mittal, Kartik Thakral, Richa Singh, Mayank Vatsa, Tamar Glaser, Cristian Canton-Ferrer, Tal Hassner:
On responsible machine learning datasets emphasizing fairness, privacy and regulatory norms with examples in biometrics and healthcare. 936-949 - Yu Zong, Yuxin Wang, Xipeng Qiu, Xuanjing Huang, Liang Qiao:
Deep learning prediction of glycopeptide tandem mass spectra powers glycoproteomics. 950-961 - Bin Feng, Zequn Liu, Nan-Lan Huang, Zhiping Xiao, Haomiao Zhang, Srbuhi Mirzoyan, Hanwen Xu, Jiaran Hao, Yinghui Xu, Ming Zhang, Sheng Wang:
A bioactivity foundation model using pairwise meta-learning. 962-974 - Shayne Longpre, Robert Mahari, Anthony Chen, Naana Obeng-Marnu, Damien Sileo, William Brannon, Niklas Muennighoff, Nathan Khazam, Jad Kabbara, Kartik Perisetla, Xinyi Wu, Enrico Shippole, Kurt D. Bollacker, Tongshuang Wu, Luis Villa, Sandy Pentland, Sara Hooker:
A large-scale audit of dataset licensing and attribution in AI. 975-987 - Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, Mengdi Wang:
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions. 988
Volume 6, Number 9, 2024
- Taewi Kim, Insic Hong, Sunghoon Im, Seungeun Rho, Minho Kim, Yeonwook Roh, Changhwan Kim, Jieun Park, Daseul Lim, Doohoe Lee, Seunggon Lee, Jingoo Lee, Inryeol Back, Junggwang Cho, Myung Rae Hong, Sanghun Kang, Joonho Lee, Sungchul Seo, Uikyum Kim, Young-Man Choi, Je-Sung Koh, Seungyong Han, Daeshik Kang:
Wing-strain-based flight control of flapping-wing drones through reinforcement learning. 992-1005 - Davide Carnevali, Limei Zhong, Esther González-Almela, Carlotta Viana, Mikhail Rotkevich, Aiping Wang, Daniel Franco-Barranco, Aitor González-Marfil, Maria Victoria Neguembor, Alvaro Castells-Garcia, Ignacio Arganda-Carreras, Maria Pia Cosma:
A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features. 1021-1033 - Mark Endo, Favour Nerrise, Qingyu Zhao, Edith V. Sullivan, Li Fei-Fei, Victor W. Henderson, Kilian M. Pohl, Kathleen L. Poston, Ehsan Adeli:
Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases. 1034-1045 - Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro, Andrew Henry Moberly, Michael James Higley, Jessica A. Cardin, David van Dijk:
Learning integral operators via neural integral equations. 1046-1062 - Shawn Reeves, Subha Kalyaanamoorthy:
Zero-shot transfer of protein sequence likelihood models to thermostability prediction. 1063-1076 - Pushpak Pati, Sofia Karkampouna, Francesco Bonollo, Eva Compérat, Martina Radic, Martin Spahn, Adriano Martinelli, Martin Wartenberg, Marianna Kruithof-de Julio, Maria Anna Rapsomaniki:
Accelerating histopathology workflows with generative AI-based virtually multiplexed tumour profiling. 1077-1093 - Yi Zhong, Gaozheng Li, Ji Yang, Houbing Zheng, Yongqiang Yu, Jiheng Zhang, Heng Luo, Biao Wang, Zuquan Weng:
Learning motif-based graphs for drug-drug interaction prediction via local-global self-attention. 1094-1105
Volume 6, Number 10, 2024
- Pick your AI poison. 1119
- Cas Wognum, Jeremy R. Ash, Matteo Aldeghi, Raquel Rodríguez-Pérez, Cheng Fang, Alan C. Cheng, Daniel J. Price, Djork-Arné Clevert, Ola Engkvist, W. Patrick Walters:
A call for an industry-led initiative to critically assess machine learning for real-world drug discovery. 1120-1121 - Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash:
Machine learning for data-centric epidemic forecasting. 1122-1131 - Sully F. Chen, Zhicheng Guo, Cheng Ding, Xiao Hu, Cynthia Rudin:
Sparse learned kernels for interpretable and efficient medical time series processing. 1132-1144 - Enrica Tricomi, Francesco Missiroli, Michele Xiloyannis, Nicola Lotti, Xiaohui Zhang, Marios Stefanakis, Maximilian Theisen, Jürgen Bauer, Clemens Becker, Lorenzo Masia:
Soft robotic shorts improve outdoor walking efficiency in older adults. 1145-1155 - Junwei Yang, Hanwen Xu, Srbuhi Mirzoyan, Tong Chen, Zixuan Liu, Zequn Liu, Wei Ju, Luchen Liu, Zhiping Xiao, Ming Zhang, Sheng Wang:
Poisoning medical knowledge using large language models. 1156-1168 - Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan:
Pre-training with fractional denoising to enhance molecular property prediction. 1169-1178 - Guruprasad Raghavan, Bahey Tharwat, Surya Narayanan Hari, Dhruvil Satani, Rex Liu, Matt Thomson:
Engineering flexible machine learning systems by traversing functionally invariant paths. 1179-1196 - Anthony Bilodeau, Albert Michaud-Gagnon, Julia Chabbert, Benoît Turcotte, Jörn Heine, Audrey Durand, Flavie Lavoie-Cardinal:
Development of AI-assisted microscopy frameworks through realistic simulation with pySTED. 1197-1215 - Ziyan Feng, Jingyang Chen, Youlong Hai, Xuelian Pang, Kun Zheng, Chenglong Xie, Xiujuan Zhang, Shengqing Li, Chengjuan Zhang, Kangdong Liu, Lili Zhu, Xiaoyong Hu, Shiliang Li, Jie Zhang, Kai Zhang, Honglin Li:
Sliding-attention transformer neural architecture for predicting T cell receptor-antigen-human leucocyte antigen binding. 1216-1230 - Liangying Yin, Yaning Feng, Yujia Shi, Alexandria Lau, Jinghong Qiu, Pak Chung Sham, Hon-Cheong So:
Estimation of causal effects of genes on complex traits using a Bayesian-network-based framework applied to GWAS data. 1231-1244 - Bohao Zou, Jingjing Wang, Yi Ding, Zhenmiao Zhang, Yufen Huang, Xiaodong Fang, Ka Chun Cheung, Simon See, Lu Zhang:
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes. 1245-1255 - Nick McGreivy, Ammar Hakim:
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations. 1256-1269 - Shihao Feng, Zhenyu Chen, Chengwei Zhang, Yuhao Xie, Sergey Ovchinnikov, Yi Qin Gao, Sirui Liu:
Author Correction: Integrated structure prediction of protein-protein docking with experimental restraints using ColabDock. 1270
Volume 6, Number 11, 2024
- AI pioneers win 2024 Nobel prizes. 1271
- Sebastian Porsdam Mann, Anuraag A. Vazirani, Mateo Aboy, Brian D. Earp, Timo Minssen, I. Glenn Cohen, Julian Savulescu:
Guidelines for ethical use and acknowledgement of large language models in academic writing. 1272-1274 - Samuel Schmidgall, Ji Woong Kim, Alan Kuntz, Ahmed Ezzat Ghazi, Axel Krieger:
General-purpose foundation models for increased autonomy in robot-assisted surgery. 1275-1283 - Youcan Yan, Ahmed Zermane, Jia Pan, Abderrahmane Kheddar:
A soft skin with self-decoupled three-axis force-sensing taxels. 1284-1295 - Janne Heirman, Wout Bittremieux:
Reusability report: Annotating metabolite mass spectra with domain-inspired chemical formula transformers. 1296-1302 - Enrui Zhang, Adar Kahana, Alena Kopanicáková, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis:
Blending neural operators and relaxation methods in PDE numerical solvers. 1303-1313 - Jialin He, Lei Xiong, Shaohui Shi, Chengyu Li, Kexuan Chen, Qianchen Fang, Jiuhong Nan, Ke Ding, Yuanhui Mao, Carles Boix, Xinyang Hu, Manolis Kellis, Jingyun Li, Xushen Xiong:
Deep learning prediction of ribosome profiling with Translatomer reveals translational regulation and interprets disease variants. 1314-1329 - Yunqi Cai, Jiangnan Li, Dong Wang:
Fast and generalizable micromagnetic simulation with deep neural nets. 1330-1343 - Yumeng Zhang, Zhikang Wang, Yunzhe Jiang, Dene R. Littler, Mark Gerstein, Anthony W. Purcell, Jamie Rossjohn, Hong-Yu Ou, Jiangning Song:
Epitope-anchored contrastive transfer learning for paired CD8+ T cell receptor-antigen recognition. 1344-1358 - Zhenxing Wu, Odin Zhang, Xiaorui Wang, Li Fu, Huifeng Zhao, Jike Wang, Hongyan Du, Dejun Jiang, Yafeng Deng, Dong-Sheng Cao, Chang-Yu Hsieh, Tingjun Hou:
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering. 1359-1369 - Solomon Asghar, Qing-Xiang Pei, Giorgio Volpe, Ran Ni:
Efficient rare event sampling with unsupervised normalizing flows. 1370-1381 - Zaixi Zhang, Wan Xiang Shen, Qi Liu, Marinka Zitnik:
Efficient generation of protein pockets with PocketGen. 1382-1395 - Sergios Gatidis, Marcel Früh, Matthias Fabritius, Sijing Gu, Konstantin Nikolaou, Christian La Fougère, Jin Ye, Junjun He, Yige Peng, Lei Bi, Jun Ma, Bo Wang, Jia Zhang, Yukun Huang, Lars Heiliger, Zdravko Marinov, Rainer Stiefelhagen, Jan Egger, Jens Kleesiek, Ludovic Sibille, Lei Xiang, Simone Bendazzoli, Mehdi Astaraki, Michael Ingrisch, Clemens C. Cyran, Thomas Küstner:
Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging. 1396-1405
Volume 6, Number 12, 2024
- Strategies needed to counter potential AI misuse. 1407
- Seeking clarity rather than strong opinions on intelligence. 1408
- Mohammad Hosseini, Christopher R. Donohue:
A plea for caution and guidance about using AI in genomics. 1409-1410 - Zining Luo, Haowei Ma, Zhiwu Li, Yuquan Chen, Yixin Sun, Aimin Hu, Jiang Yu, Yang Qiao, Junxian Gu, Hongying Li, Xuxi Peng, Dunrui Wang, Ying Liu, Zhenglong Liu, Jiebin Xie, Zhen Jiang, Gang Tian:
Clinical large language models with misplaced focus. 1411-1412 - Pascal Wallisch, Ibrahim Sheikh:
Towards a personalized AI assistant to learn machine learning. 1413-1414 - Christian Montag, Michèle Finck:
Successful implementation of the EU AI Act requires interdisciplinary efforts. 1415-1417 - Jianing Qiu, Kyle Lam, Guohao Li, Amish Acharya, Tien Yin Wong, Ara Darzi, Wu Yuan, Eric J. Topol:
LLM-based agentic systems in medicine and healthcare. 1418-1420 - Thomas Grote, Timo Freiesleben, Philipp Berens:
Foundation models in healthcare require rethinking reliability. 1421-1423 - Nicolas Rouleau, Michael Levin:
Discussions of machine versus living intelligence need more clarity. 1424-1426 - Thomas Schmickl:
Memetic robots. 1427-1428 - Tianang Leng, Cesar de la Fuente-Nunez:
AI in biomaterials discovery: generating self-assembling peptides with resource-efficient deep learning. 1429-1430 - Kuanming Yao, Qiuna Zhuang:
Self-decoupling three-axis forces in a simple sensor. 1431-1432 - Smita Deb, Partha Sharathi Dutta:
Deep learning at the forefront of detecting tipping points. 1433-1434 - Artem A. Trotsyuk, Quinn Waeiss, Raina Talwar Bhatia, Brandon J. Aponte, Isabella M. L. Heffernan, Devika Madgavkar, Ryan Marshall Felder, Lisa Soleymani Lehmann, Megan J. Palmer, Hank Greely, Russell Wald, Lea Goetz, Markus Trengove, Robert Vandersluis, Herbert Lin, Mildred K. Cho, Russ B. Altman, Drew Endy, David A. Relman, Margaret Levi, Debra Satz, David Magnus:
Toward a framework for risk mitigation of potential misuse of artificial intelligence in biomedical research. 1435-1442 - Rebecca Boiarsky, Nalini M. Singh, Alejandro Buendia, Ava P. Amini, Gad Getz, David A. Sontag:
Deeper evaluation of a single-cell foundation model. 1443-1446 - Fan Yang, Fang Wang, Longkai Huang, Linjing Liu, Junzhou Huang, Jianhua Yao:
Reply to: Deeper evaluation of a single-cell foundation model. 1447-1450 - Nik Dennler, André van Schaik, Michael Schmuker:
Limitations in odour recognition and generalization in a neuromorphic olfactory circuit. 1451-1453 - Roy Moyal, Nabil Imam, Thomas A. Cleland:
Reply to: Limitations in odour recognition and generalization in a neuromorphic olfactory circuit. 1454-1456 - Ruijiang Li, Jiang Lu, Ziyi Liu, Duoyun Yi, Mengxuan Wan, Yixin Zhang, Peng Zan, Song He, Xiaochen Bo:
Reusability report: exploring the utility of variational graph encoders for predicting molecular toxicity in drug design. 1457-1466 - Gavin Mischler, Yinghao Aaron Li, Stephan Bickel, Ashesh D. Mehta, Nima Mesgarani:
Contextual feature extraction hierarchies converge in large language models and the brain. 1467-1477 - Haoran Liao, Derek S. Wang, Iskandar Sitdikov, Ciro Salcedo, Alireza Seif, Zlatko Minev:
Machine learning for practical quantum error mitigation. 1478-1486 - Marko Njirjak, Lucija Zuzic, Marko Babic, Patrizia Jankovic, Erik Otovic, Daniela Kalafatovic, Goran Mausa:
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning. 1487-1500 - Janghoon Ock, Srivathsan Badrinarayanan, Rishikesh Magar, Akshay Antony, Amir Barati Farimani:
Multimodal language and graph learning of adsorption configuration in catalysis. 1501-1511 - Yasha Ektefaie, Andrew Shen, Daria Bykova, Maximillian G. Marin, Marinka Zitnik, Maha R. Farhat:
Evaluating generalizability of artificial intelligence models for molecular datasets. 1512-1524 - Shaohua Fan, Renzhe Xu, Qian Dong, Yue He, Cheng Chang, Peng Cui:
Stable Cox regression for survival analysis under distribution shifts. 1525-1541 - Dana S. Matthews, Matthew A. Spence, A. C. Mater, J. Nichols, S. B. Pulsford, M. Sandhu, J. A. Kaczmarski, Charlotte M. Miton, N. Tokuriki, Colin J. Jackson:
Leveraging ancestral sequence reconstruction for protein representation learning. 1542-1555 - Yu Huang, Sebastian Bathiany, Peter Ashwin, Niklas Boers:
Deep learning for predicting rate-induced tipping. 1556-1565 - Zeyu Li, Wang Han, Yue Zhang, Qingfei Fu, Jingxuan Li, Lizi Qin, Ruoyu Dong, Hao Sun, Yue Deng, Lijun Yang:
Learning spatiotemporal dynamics with a pretrained generative model. 1566-1579 - Guanglu Jia, Zhe Chen, Yulai Zhang, Zhenshan Bing, Zhenzhen Quan, Xuechao Chen, Alois Knoll, Qiang Huang, Qing Shi:
Modulating emotional states of rats through a rat-like robot with learned interaction patterns. 1580-1593 - Juntao Deng, Miao Gu, Pengyan Zhang, Mingyu Dong, Tao Liu, Yabin Zhang, Min Liu:
Nanobody-antigen interaction prediction with ensemble deep learning and prompt-based protein language models. 1594-1604 - Julian Büchel, Giacomo Camposampiero, Athanasios Vasilopoulos, Corey Lammie, Manuel Le Gallo, Abbas Rahimi, Abu Sebastian:
Kernel approximation using analogue in-memory computing. 1605-1615 - Haopeng Yu, Heng Yang, Wenqing Sun, Zongyun Yan, Xiaofei Yang, Huakun Zhang, Yiliang Ding, Ke Li:
An interpretable RNA foundation model for exploring functional RNA motifs in plants. 1616-1625 - Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu:
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning. 1626
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