Nature Machine Intelligence

Article	Citations
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators	884
Shortcut learning in deep neural networks	697
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans	667
An open source machine learning framework for efficient and transparent systematic reviews	336
Deep learning for tomographic image reconstruction	301
Machine learning pipeline for battery state-of-health estimation	301
Molecular contrastive learning of representations via graph neural networks	294
AI for radiographic COVID-19 detection selects shortcuts over signal	271
Geometry-enhanced molecular representation learning for property prediction	212
Expanding functional protein sequence spaces using generative adversarial networks	202
Inverse design of nanoporous crystalline reticular materials with deep generative models	202
End-to-end privacy preserving deep learning on multi-institutional medical imaging	201
Development of metaverse for intelligent healthcare	185
Advances, challenges and opportunities in creating data for trustworthy AI	163
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data	156
Improved protein structure prediction by deep learning irrespective of co-evolution information	154
Mapping the space of chemical reactions using attention-based neural networks	147
Geometric deep learning on molecular representations	144
Concept whitening for interpretable image recognition	143
Deep learning-based prediction of the T cell receptor–antigen binding specificity	141
Three types of incremental learning	140
Generating three-dimensional structures from a two-dimensional slice with generative adversarial network-based dimensionality expansion	132
Parameter-efficient fine-tuning of large-scale pre-trained language models	128
Dual use of artificial-intelligence-powered drug discovery	124
AI-generated characters for supporting personalized learning and well-being	118

A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing	118
Machine learning and computation-enabled intelligent sensor design	116
A soft robot that adapts to environments through shape change	114
Integration of multiomics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms	114
Towards neural Earth system modelling by integrating artificial intelligence in Earth system science	113
Code-free deep learning for multi-modality medical image classification	113
Estimation of continuous valence and arousal levels from faces in naturalistic conditions	113
The transformational role of GPU computing and deep learning in drug discovery	112
Bioinspired acousto-magnetic microswarm robots with upstream motility	112
Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network	109
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors	109
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks	108
Prediction of water stability of metal–organic frameworks using machine learning	107
Automating turbulence modelling by multi-agent reinforcement learning	106
A soft thumb-sized vision-based sensor with accurate all-round force perception	105
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning	104
Machine learning and algorithmic fairness in public and population health	102
Stable learning establishes some common ground between causal inference and machine learning	102
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling	100
Learning functional properties of proteins with language models	100
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning	99
Controllable protein design with language models	98
Large-scale chemical language representations capture molecular structure and properties	97
Large pre-trained language models contain human-like biases of what is right and wrong to do	97
Human–AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support	95
Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning	94
Biological underpinnings for lifelong learning machines	94
A definition, benchmark and database of AI for social good initiatives	92
Encoding of tactile information in hand via skin-integrated wireless haptic interface	88
A versatile deep learning architecture for classification and label-free prediction of hyperspectral images	87
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin	87
A geometric deep learning approach to predict binding conformations of bioactive molecules	86
Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations	84
Improving performance of deep learning models with axiomatic attribution priors and expected gradients	84
Morphological and molecular breast cancer profiling through explainable machine learning	83
Governing AI safety through independent audits	81
Combinatorial optimization with physics-inspired graph neural networks	81
A transformer-based model to predict peptide–HLA class I binding and optimize mutated peptides for vaccine design	79
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework	79
A case-based interpretable deep learning model for classification of mass lesions in digital mammography	77
Predictive control of aerial swarms in cluttered environments	76
Benchmarking saliency methods for chest X-ray interpretation	76
Teaching recurrent neural networks to infer global temporal structure from local examples	75
Deep neural networks identify sequence context features predictive of transcription factor binding	71
Molecular convolutional neural networks with DNA regulatory circuits	71
Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes	70
Simultaneous deep generative modelling and clustering of single-cell genomic data	68
Multimodal data fusion for cancer biomarker discovery with deep learning	67
Algorithms to estimate Shapley value feature attributions	67
Fast and energy-efficient neuromorphic deep learning with first-spike times	67

Extraction of protein dynamics information from cryo-EM maps using deep learning	63
Learning function from structure in neuromorphic networks	63
Interpretable bilinear attention network with domain adaptation improves drug–target prediction	63
Interpretable deep-learning models to help achieve the Sustainable Development Goals	61
Chemical language models enable navigation in sparsely populated chemical space	61
Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy	60
Experimental discovery of structure–property relationships in ferroelectric materials via active learning	58
Large language models associate Muslims with violence	58
Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification	57
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware	57
Chemically programmable microrobots weaving a web from hormones	57
Multiscale simulations of complex systems by learning their effective dynamics	56
Deep recurrent optical flow learning for particle image velocimetry data	55
Improving representations of genomic sequence motifs in convolutional networks with exponential activations	53
A biological perspective on evolutionary computation	53
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks	53
Mixed-modality speech recognition and interaction using a wearable artificial throat	53
Cell type annotation of single-cell chromatin accessibility data via supervised Bayesian embedding	53
Radiological tumour classification across imaging modality and histology	51
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments	51
Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities	51
A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data	50
Real-world embodied AI through a morphologically adaptive quadruped robot	50
Generalized radiograph representation learning via cross-supervision between images and free-text radiology reports	50
Deep learning-based robust positioning for all-weather autonomous driving	50
Visual speech recognition for multiple languages in the wild	49
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition	48
Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices	48
Automatic strain sensor design via active learning and data augmentation for soft machines	48
Predicting myocardial infarction through retinal scans and minimal personal information	47
Institutionalizing ethics in AI through broader impact requirements	46
Accelerated rational PROTAC design via deep learning and molecular simulations	46
An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data	46
A machine learning platform to estimate anti-SARS-CoV-2 activities	46
Large language models challenge the future of higher education	46
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy	45
External validation demonstrates limited clinical utility of the interpretable mortality prediction model for patients with COVID-19	45
Recovery of continuous 3D refractive index maps from discrete intensity-only measurements using neural fields	45
Skills for physical artificial intelligence	44
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires	44
From attribution maps to human-understandable explanations through Concept Relevance Propagation	44
Cross-validation is safe to use	44
Bringing artificial intelligence to business management	44
The neural resource allocation problem when enhancing human bodies with extra robotic limbs	43
Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy	43
Autoregressive neural-network wavefunctions for ab initio quantum chemistry	42
A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputation	42
Artificial intelligence-powered electronic skin	41
Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots	41
Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks	41
Regression Transformer enables concurrent sequence regression and generation for molecular language modelling	41
Quantifying the spatial homogeneity of urban road networks via graph neural networks	40
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	39
Enhancing optical-flow-based control by learning visual appearance cues for flying robots	39
Intelligent problem-solving as integrated hierarchical reinforcement learning	39
A deep generative model enables automated structure elucidation of novel psychoactive substances	39
Decoding speech perception from non-invasive brain recordings	38
Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning	38
Multimodal learning with graphs	38
Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider	37
Closed-form continuous-time neural networks	37
Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries	37
Knowledge graph-enhanced molecular contrastive learning with functional prompt	36
Variational neural annealing	36
Deep learning prediction of patient response time course from early data via neural-pharmacokinetic/pharmacodynamic modelling	36
Neurons learn by predicting future activity	36
An automated framework for efficiently designing deep convolutional neural networks in genomics	36
Deep transfer operator learning for partial differential equations under conditional shift	36
Artificial microtubules for rapid and collective transport of magnetic microcargoes	35
An ethical trajectory planning algorithm for autonomous vehicles	35
Direct-to-consumer medical machine learning and artificial intelligence applications	34
Automating crystal-structure phase mapping by combining deep learning with constraint reasoning	34
Leveraging large language models for predictive chemistry	33
Labelling instructions matter in biomedical image analysis	33
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model	33
A critical problem in benchmarking and analysis of evolutionary computation methods	33
Segmentation of neurons from fluorescence calcium recordings beyond real time	33
Data-driven discovery of intrinsic dynamics	32
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning	32
Designing clinically translatable artificial intelligence systems for high-dimensional medical imaging	32

The AI writing on the wall	32
Deep learning STEM-EDX tomography of nanocrystals	32
A deep generative model for molecule optimization via one fragment modification	31
Echo state graph neural networks with analogue random resistive memory arrays	31
Predicting functional effect of missense variants using graph attention neural networks	31
Regulating AI in medicine in the United States and Europe	31
Transformer-based protein generation with regularized latent space optimization	31
Global voxel transformer networks for augmented microscopy	30
Inferring transcription factor regulatory networks from single-cell ATAC-seq data based on graph neural networks	30
Understanding adversarial examples requires a theory of artefacts for deep learning	30
Inverse design of nonlinear mechanical metamaterials via video denoising diffusion models	30
Machine learning to guide the use of adjuvant therapies for breast cancer	29
Transferring policy of deep reinforcement learning from simulation to reality for robotics	29
Harnessing the power of artificial intelligence to transform hearing healthcare and research	29
A context-aware deconfounding autoencoder for robust prediction of personalized clinical drug response from cell-line compound screening	29
Unassisted noise reduction of chemical reaction datasets	28
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning	28
Physics-based machine learning for subcellular segmentation in living cells	28
Evaluation of post-hoc interpretability methods in time-series classification	28
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applications	28
Geometric deep learning reveals the spatiotemporal features of microscopic motion	27
Simple nearest-neighbour analysis meets the accuracy of compound potency predictions using complex machine learning models	27
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis	27
Generative AI entails a credit–blame asymmetry	27
Federated disentangled representation learning for unsupervised brain anomaly detection	26
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer	26
A generalized-template-based graph neural network for accurate organic reactivity prediction	26
Encoding physics to learn reaction–diffusion processes	26
Optimizing molecules using efficient queries from property evaluations	26
Evaluating deep learning for predicting epigenomic profiles	25
Learning MRI artefact removal with unpaired data	25
Learning biophysical determinants of cell fate with deep neural networks	25
Super-resolution generative adversarial networks of randomly-seeded fields	25
Design of potent antimalarials with generative chemistry	25
Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations	24
Improving de novo molecular design with curriculum learning	24
Exploring the cloud of variable importance for the set of all good models	24
Self-supervised learning of hologram reconstruction using physics consistency	24
A textile exomuscle that assists the shoulder during functional movements for everyday life	24
Neural Error Mitigation of Near-Term Quantum Simulations	23
Iterative human and automated identification of wildlife images	23
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models	23
Search and rescue with airborne optical sectioning	23
Federated benchmarking of medical artificial intelligence with MedPerf	23
A fast blind zero-shot denoiser	23
Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines	23
Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network	22
Active mechanical haptics with high-fidelity perceptions for immersive virtual reality	22
High-resolution radar road segmentation using weakly supervised learning	22
Explaining machine learning models with interactive natural language conversations using TalkToModel	22
Linguistically inspired roadmap for building biologically reliable protein language models	22
Replication of a mortality prediction model in Dutch patients with COVID-19	22
Learning from data with structured missingness	21
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions	21
Integration of millions of transcriptomes using batch-aware triplet neural networks	21
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations	21
Continuous improvement of self-driving cars using dynamic confidence-aware reinforcement learning	21
An adaptive graph learning method for automated molecular interactions and properties predictions	21
Lessons from infant learning for unsupervised machine learning	21
Augmenting large language models with chemistry tools	21
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling	20
Simultaneous dimensionality reduction and integration for single-cell ATAC-seq data using deep learning	20
Physical human–robot interaction for clinical care in infectious environments	20
Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset	19
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks	19
Neural scaling of deep chemical models	19
Construction of a 3D whole organism spatial atlas by joint modelling of multiple slices with deep neural networks	19
An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors	19
Interpretability of artificial neural network models in artificial intelligence versus neuroscience	19
The importance of resource awareness in artificial intelligence for healthcare	19
Influencing human–AI interaction by priming beliefs about AI can increase perceived trustworthiness, empathy and effectiveness	19
Embodied intelligence weaves a better future	19
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning	19
Towards quantum enhanced adversarial robustness in machine learning	19
Human autonomy in the age of artificial intelligence	19
Integration of deep learning and soft robotics for a biomimetic approach to nonlinear sensing	18
Autonomous 3D positional control of a magnetic microrobot using reinforcement learning	18
Multitask joint strategies of self-supervised representation learning on biomedical networks for drug discovery	18
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion	18
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes	18
High-speed quadrupedal locomotion by imitation-relaxation reinforcement learning	18
On the importance of ethnographic methods in AI research	18
State-specific protein–ligand complex structure prediction with a multiscale deep generative model	18
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics	17
Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale	17
Deep learning models for predicting RNA degradation via dual crowdsourcing	17
Out-of-distribution generalization from labelled and unlabelled gene expression data for drug response prediction	17
Developing robust benchmarks for driving forward AI innovation in healthcare	17
Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation	17
Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network	17
Interpreting neural networks for biological sequences by learning stochastic masks	17
A neuro-vector-symbolic architecture for solving Raven’s progressive matrices	16
Generalizability of an acute kidney injury prediction model across health systems	16
Limited applicability of a COVID-19 specific mortality prediction rule to the intensive care setting	16
Biomonitoring and precision health in deep space supported by artificial intelligence	16