Nature Machine Intelligence

Papers
(The TQCC of Nature Machine Intelligence is 37. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-01-01 to 2026-01-01.)
ArticleCitations
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions641
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence627
Physical benchmarks for testing algorithms550
A challenge for the law and artificial intelligence476
Towards reproducible robotics research446
Author Correction: Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock436
Artificial intelligence tackles the nature–nurture debate394
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit354
Investigating machine moral judgement through the Delphi experiment329
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes329
Discussions of machine versus living intelligence need more clarity297
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models286
Human autonomy in the age of artificial intelligence260
Materiality and risk in the age of pervasive AI sensors241
Wing-strain-based flight control of flapping-wing drones through reinforcement learning239
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills225
Tailored structured peptide design with a key-cutting machine approach205
AI pioneers win 2024 Nobel prizes201
A question of trust for AI research in medicine201
Robust virtual staining of landmark organelles with Cytoland200
Fast and generalizable micromagnetic simulation with deep neural nets200
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI195
The curious case of the test set AUROC185
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene179
Are neural network representations universal or idiosyncratic?176
Transformer-based protein generation with regularized latent space optimization170
Pseudodata-based molecular structure generator to reveal unknown chemicals161
Large language models still struggle with false beliefs161
A Global South perspective for ethical algorithms and the State160
Maximum diffusion reinforcement learning159
Zero-shot transfer of protein sequence likelihood models to thermostability prediction148
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants144
Advancing ethics review practices in AI research141
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics136
Bringing artificial intelligence to business management133
Quantum circuit optimization with AlphaTensor126
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion123
Recurrent graph optimal transport for learning 3D flow motion in particle tracking123
Inferring spatial single-cell-level interactions through interpreting cell state and niche correlations learned by self-supervised graph transformer122
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning122
A new perspective on the simulation of stochastic problems in fluid mechanics with diffusion models121
How to break information cocoons121
Error-controlled non-additive interaction discovery in machine learning models118
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock115
What’s the next word in large language models?114
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling113
Machine learning prediction of enzyme optimum pH110
Laplace neural operator for solving differential equations109
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin108
Codon language embeddings provide strong signals for use in protein engineering108
Combinatorial optimization with physics-inspired graph neural networks107
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments102
Learning from models beyond fine-tuning101
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework101
What is in your LLM-based framework?100
Unsupervised learning of topological non-Abelian braiding in non-Hermitian bands100
AI reality check100
Foundation models in healthcare require rethinking reliability99
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter–defibrillators98
Seeking a quantum advantage for machine learning96
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning94
Deciphering RNA–ligand binding specificity with GerNA-Bind93
Designing a strong test for measuring true common-sense reasoning92
Efficient generation of protein pockets with PocketGen90
Collaborative creativity in AI90
Bridging peptide presentation and T cell recognition with multi-task learning89
Learning high-level visual representations from a child’s perspective without strong inductive biases89
Unifying multi-sample network inference from prior knowledge and omics data with CORNETO89
Autoregressive neural-network wavefunctions for ab initio quantum chemistry89
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer88
Neural scaling of deep chemical models86
Morphological flexibility in robotic systems through physical polygon meshing85
Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation85
Image-based generation for molecule design with SketchMol85
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning83
Accurate and robust protein sequence design with CarbonDesign83
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols81
Multimodal learning with graphs81
Tandem mass spectrum prediction for small molecules using graph transformers80
A multi-modal pre-training transformer for universal transfer learning in metal–organic frameworks80
Human–AI adaptive dynamics drives the emergence of information cocoons80
LLM-based agentic systems in medicine and healthcare79
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics79
ARNLE model identifies prevalence potential of SARS-CoV-2 variants79
Foundation models and the privatization of public knowledge77
Towards generalizable and interpretable three-dimensional tracking with inverse neural rendering76
Improving de novo molecular design with curriculum learning76
Differentiable visual computing for inverse problems and machine learning76
Human-behaviour-based social locomotion model improves the humanization of social robots75
Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms74
Advanced AI assistants that act on our behalf may not be ethically or legally feasible74
Anniversary AI reflections73
Learning plastic matching of robot dynamics in closed-loop central pattern generators72
A multimodal cell-free RNA language model for liquid biopsy applications72
A neuro-vector-symbolic architecture for solving Raven’s progressive matrices72
Moving towards genome-wide data integration for patient stratification with Integrate Any Omics71
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis71
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling71
Reusability report: Exploring the transferability of self-supervised learning models from single-cell to spatial transcriptomics71
Enhancing deep learning-based field reconstruction with a differentiable learning framework69
Model-based reinforcement learning for ultrasound-driven autonomous microrobots69
The transformational role of GPU computing and deep learning in drug discovery69
Writing the rules in AI-assisted writing69
From attribution maps to human-understandable explanations through Concept Relevance Propagation68
Reconstructing growth and dynamic trajectories from single-cell transcriptomics data68
Geometric deep learning reveals the spatiotemporal features of microscopic motion68
Publisher Correction: A neural machine code and programming framework for the reservoir computer66
A social network for AI66
A method for multiple-sequence-alignment-free protein structure prediction using a protein language model66
Successful implementation of the EU AI Act requires interdisciplinary efforts65
Sampling-enabled scalable manifold learning unveils the discriminative cluster structure of high-dimensional data65
Distinguishing two features of accountability for AI technologies65
Mask-prior-guided denoising diffusion improves inverse protein folding65
Lessons from a challenge on forecasting epileptic seizures from non-cerebral signals64
Leveraging language model for advanced multiproperty molecular optimization via prompt engineering64
Learning integral operators via neural integral equations63
Defending ChatGPT against jailbreak attack via self-reminders63
An interaction-derived graph learning framework for scoring protein–peptide complexes63
Benchmarking AI-powered docking methods from the perspective of virtual screening62
Mode switching in organisms for solving explore-versus-exploit problems61
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling61
Advances, challenges and opportunities in creating data for trustworthy AI61
Learning intermediate physical states for inverse metasurface design60
Closed-form continuous-time neural networks59
Active learning for optimal intervention design in causal models59
Delineating the effective use of self-supervised learning in single-cell genomics58
Artificial intelligence-powered electronic skin58
Listening in to perceived speech with contrastive learning57
Interpretable meta-score for model performance56
On board with COMET to improve omics prediction models56
A new eye on inherited retinal disease55
A generalizable deep learning framework for inferring fine-scale germline mutation rate maps55
Prediction of robust scientific facts from literature55
The incentive gap in data work in the era of large models55
Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model55
A unified deep framework for peptide–major histocompatibility complex–T cell receptor binding prediction54
Deep transfer operator learning for partial differential equations under conditional shift54
Deep learning for predicting rate-induced tipping54
Machine learning-enabled globally guaranteed evolutionary computation53
A computational framework for neural network-based variational Monte Carlo with Forward Laplacian53
Solving sparse finite element problems on neuromorphic hardware53
Lossless data compression by large models52
Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases52
Versatile cardiovascular signal generation with a unified diffusion transformer52
Incorporating physics into data-driven computer vision52
Fast, scale-adaptive and uncertainty-aware downscaling of Earth system model fields with generative machine learning51
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions51
Three types of incremental learning50
Large language models challenge the future of higher education50
Current-diffusion model for metasurface structure discoveries with spatial-frequency dynamics50
Molecular contrastive learning of representations via graph neural networks50
Invalid SMILES are beneficial rather than detrimental to chemical language models49
Augmenting large language models with chemistry tools48
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology48
Publisher Correction: Advancing ethics review practices in AI research47
AI podcasts for the summer47
Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks47
Deep learning-based prediction of the selection factors for quantifying selection in immune receptor repertoires47
A process-centric manipulation taxonomy for the organization, classification and synthesis of tactile robot skills46
Deconstructing the generalization gap46
Space missions out of this world with AI45
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations44
Synergy-based robotic quadruped leveraging passivity for natural intelligence and behavioural diversity44
Automated construction of cognitive maps with visual predictive coding44
The importance of negative training data for robust antibody binding prediction44
Discovering neural policies to drive behaviour by integrating deep reinforcement learning agents with biological neural networks43
Automated causal inference in application to randomized controlled clinical trials43
Realistic morphology-preserving generative modelling of the brain43
Design of prime-editing guide RNAs with deep transfer learning43
Labelling instructions matter in biomedical image analysis42
Aligning generalization between humans and machines42
Generalized biological foundation model with unified nucleic acid and protein language41
Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement41
Pan-Peptide Meta Learning for T-cell receptor–antigen binding recognition40
Visual speech recognition for multiple languages in the wild40
Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions40
Why design choices matter in recommender systems39
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems39
A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics38
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning38
Weak signal extraction enabled by deep neural network denoising of diffraction data38
Accelerating protein engineering with fitness landscape modelling and reinforcement learning38
A framework for tool cognition in robots without prior tool learning or observation37
Type II mechanoreceptors and cuneate spiking neuronal network enable touch localization on a large-area e-skin37
Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning37
A soft touch for robots37
No chemical killer AI (yet)37
Embodied large language models enable robots to complete complex tasks in unpredictable environments37
Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare37
An integrated framework to accelerate protein design through mutagenesis37
Geometric deep learning of particle motion by MAGIK37
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