Nature Machine Intelligence

Article	Citations
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions	586
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	564
Physical benchmarks for testing algorithms	459
Materiality and risk in the age of pervasive AI sensors	436
A challenge for the law and artificial intelligence	408
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes	401
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	373
Human autonomy in the age of artificial intelligence	337
Wing-strain-based flight control of flapping-wing drones through reinforcement learning	284
Author Correction: Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	268
Artificial intelligence tackles the nature–nurture debate	258
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models	257
Investigating machine moral judgement through the Delphi experiment	254
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit	237
Discussions of machine versus living intelligence need more clarity	224
Tailored structured peptide design with a key-cutting machine approach	216
Towards reproducible robotics research	214
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills	208
A question of trust for AI research in medicine	190
A Global South perspective for ethical algorithms and the State	187
Fast and generalizable micromagnetic simulation with deep neural nets	185
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI	184
Quantum circuit optimization with AlphaTensor	181
Advancing ethics review practices in AI research	181
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion	175

Are neural network representations universal or idiosyncratic?	169
Transformer-based protein generation with regularized latent space optimization	166
Out-of-distribution generalization from labelled and unlabelled gene expression data for drug response prediction	157
Robust virtual staining of landmark organelles with Cytoland	156
The curious case of the test set AUROC	147
Bringing artificial intelligence to business management	145
AI pioneers win 2024 Nobel prizes	143
Zero-shot transfer of protein sequence likelihood models to thermostability prediction	139
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants	129
Recurrent graph optimal transport for learning 3D flow motion in particle tracking	126
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene	125
Maximum diffusion reinforcement learning	122
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning	122
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics	118
Machine learning prediction of enzyme optimum pH	117
What’s the next word in large language models?	117
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling	116
How to break information cocoons	116
Combinatorial optimization with physics-inspired graph neural networks	116
A new perspective on the simulation of stochastic problems in fluid mechanics with diffusion models	111
Error-controlled non-additive interaction discovery in machine learning models	110
Learning from models beyond fine-tuning	106
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	101
Laplace neural operator for solving differential equations	99
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework	98
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments	97
Codon language embeddings provide strong signals for use in protein engineering	97
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin	97
Collaborative creativity in AI	96
Bridging peptide presentation and T cell recognition with multi-task learning	95
AI reality check	95
Unifying multi-sample network inference from prior knowledge and omics data with CORNETO	94
What is in your LLM-based framework?	94
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter–defibrillators	93
A deep learning method for recovering missing signals in transcriptome-wide RNA structure profiles from probing experiments	92
Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation	91
Learning high-level visual representations from a child’s perspective without strong inductive biases	90
Autoregressive neural-network wavefunctions for ab initio quantum chemistry	90
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands	88
Seeking a quantum advantage for machine learning	88
Foundation models in healthcare require rethinking reliability	85
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer	84
Efficient generation of protein pockets with PocketGen	83
Designing a strong test for measuring true common-sense reasoning	83
Tandem mass spectrum prediction for small molecules using graph transformers	82
Image-based generation for molecule design with SketchMol	81
Morphological flexibility in robotic systems through physical polygon meshing	81
Accurate and robust protein sequence design with CarbonDesign	78
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning	77
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning	77

A deep generative model enables automated structure elucidation of novel psychoactive substances	76
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols	76
A deep generative model for molecule optimization via one fragment modification	76
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics	76
Neural scaling of deep chemical models	76
LLM-based agentic systems in medicine and healthcare	75
Multimodal learning with graphs	74
Human–AI adaptive dynamics drives the emergence of information cocoons	74
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks	72
ARNLE model identifies prevalence potential of SARS-CoV-2 variants	71
Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms	71
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling	70
Learning plastic matching of robot dynamics in closed-loop central pattern generators	70
Foundation models and the privatization of public knowledge	69
Reconstructing growth and dynamic trajectories from single-cell transcriptomics data	67
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model	67
From attribution maps to human-understandable explanations through Concept Relevance Propagation	67
Differentiable visual computing for inverse problems and machine learning	66
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis	66
Enhancing deep learning-based field reconstruction with a differentiable learning framework	65
Writing the rules in AI-assisted writing	65
Towards generalizable and interpretable three-dimensional tracking with inverse neural rendering	65
Moving towards genome-wide data integration for patient stratification with Integrate Any Omics	63
Anniversary AI reflections	63
Geometric deep learning reveals the spatiotemporal features of microscopic motion	63
Human-behaviour-based social locomotion model improves the humanization of social robots	63
Improving de novo molecular design with curriculum learning	63
Reusability report: Exploring the transferability of self-supervised learning models from single-cell to spatial transcriptomics	63
A neuro-vector-symbolic architecture for solving Raven’s progressive matrices	63
Advanced AI assistants that act on our behalf may not be ethically or legally feasible	63
The transformational role of GPU computing and deep learning in drug discovery	62
Model-based reinforcement learning for ultrasound-driven autonomous microrobots	62
A social network for AI	62
Publisher Correction: A neural machine code and programming framework for the reservoir computer	61
Successful implementation of the EU AI Act requires interdisciplinary efforts	60
Active learning for optimal intervention design in causal models	60
Artificial intelligence-powered electronic skin	59
Closed-form continuous-time neural networks	59
Lessons from a challenge on forecasting epileptic seizures from non-cerebral signals	59
Defending ChatGPT against jailbreak attack via self-reminders	59
Mask-prior-guided denoising diffusion improves inverse protein folding	58
Distinguishing two features of accountability for AI technologies	58
Learning integral operators via neural integral equations	58
Advances, challenges and opportunities in creating data for trustworthy AI	57
Mode switching in organisms for solving explore-versus-exploit problems	57
Benchmarking AI-powered docking methods from the perspective of virtual screening	57
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering	57
An interaction-derived graph learning framework for scoring protein–peptide complexes	57
Sampling-enabled scalable manifold learning unveils the discriminative cluster structure of high-dimensional data	57
Delineating the effective use of self-supervised learning in single-cell genomics	57
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling	56
Listening in to perceived speech with contrastive learning	55
A unified deep framework for peptide–major histocompatibility complex–T cell receptor binding prediction	55
On board with COMET to improve omics prediction models	55
Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases	55
Interpretable meta-score for model performance	55
Machine learning-enabled globally guaranteed evolutionary computation	53
Large language models challenge the future of higher education	53
Improving customer decisions in web-based e-commerce through guerrilla modding	53
Deep transfer operator learning for partial differential equations under conditional shift	53
Lossless data compression by large models	53
Incorporating physics into data-driven computer vision	53
A new eye on inherited retinal disease	53
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions	52
Prediction of robust scientific facts from literature	52
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology	52
Fast, scale-adaptive and uncertainty-aware downscaling of Earth system model fields with generative machine learning	51
A computational framework for neural network-based variational Monte Carlo with Forward Laplacian	51
A generalizable deep learning framework for inferring fine-scale germline mutation rate maps	51
The incentive gap in data work in the era of large models	51
Molecular contrastive learning of representations via graph neural networks	50
Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model	50
Invalid SMILES are beneficial rather than detrimental to chemical language models	50
Three types of incremental learning	49
Deep learning for predicting rate-induced tipping	49
Augmenting large language models with chemistry tools	48
Publisher Correction: Advancing ethics review practices in AI research	48
AI podcasts for the summer	48
Space missions out of this world with AI	47
Deep learning-based prediction of the selection factors for quantifying selection in immune receptor repertoires	47

Synergy-based robotic quadruped leveraging passivity for natural intelligence and behavioural diversity	47
The importance of negative training data for robust antibody binding prediction	46
Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks	46
A process-centric manipulation taxonomy for the organization, classification and synthesis of tactile robot skills	45
Deconstructing the generalization gap	43
Aligning generalization between humans and machines	43
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations	43
Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks	42
Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions	42
Automated construction of cognitive maps with visual predictive coding	42
Labelling instructions matter in biomedical image analysis	42
Realistic morphology-preserving generative modelling of the brain	42
Generalized biological foundation model with unified nucleic acid and protein language	41
Physics-based machine learning for subcellular segmentation in living cells	41
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition	40
Visual speech recognition for multiple languages in the wild	40
Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement	40
Design of prime-editing guide RNAs with deep transfer learning	39
Automated causal inference in application to randomized controlled clinical trials	39
Why design choices matter in recommender systems	38
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning	38
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems	38
Accelerating protein engineering with fitness landscape modelling and reinforcement learning	37
A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics	37
Type II mechanoreceptors and cuneate spiking neuronal network enable touch localization on a large-area e-skin	37
Weak signal extraction enabled by deep neural network denoising of diffraction data	37
On the caveats of AI autophagy	36
Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning	36
Geometric deep learning of particle motion by MAGIK	36
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare	36
A soft touch for robots	36