OOIR: Observatory of International Research

Papers

(The H4-Index of Nature Machine Intelligence is 72. 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 2021-08-01 to 2025-08-01.)

Article	Citations
Author Correction: A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions	517
Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	444
Physical benchmarks for testing algorithms	378
Wiring up recurrent neural networks	359
Materiality and risk in the age of pervasive AI sensors	349
A challenge for the law and artificial intelligence	334
Human autonomy in the age of artificial intelligence	328
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes	304
Discussions of machine versus living intelligence need more clarity	238
A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit	228
Author Correction: Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	220
Investigating machine moral judgement through the Delphi experiment	213
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models	207
Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence	204
A soft-packaged and portable rehabilitation glove capable of closed-loop fine motor skills	195
Wing-strain-based flight control of flapping-wing drones through reinforcement learning	181
Artificial intelligence tackles the nature–nurture debate	179
A question of trust for AI research in medicine	174
Robotic body augmentation	173
A Global South perspective for ethical algorithms and the State	170
Sparsity provides a competitive advantage	166
Maximum diffusion reinforcement learning	165
Advancing ethics review practices in AI research	164
Robust virtual staining of landmark organelles with Cytoland	161
Quantum circuit optimization with AlphaTensor	161

Bringing artificial intelligence to business management	161
The curious case of the test set AUROC	159
Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning	151
Out-of-distribution generalization from labelled and unlabelled gene expression data for drug response prediction	150
Fast and generalizable micromagnetic simulation with deep neural nets	150
Reusability report: Deep learning-based analysis of images and spectroscopy data with AtomAI	150
Transformer-based protein generation with regularized latent space optimization	135
Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion	134
Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene	133
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants	130
AI pioneers win 2024 Nobel prizes	130
Recurrent graph optimal transport for learning 3D flow motion in particle tracking	124
Zero-shot transfer of protein sequence likelihood models to thermostability prediction	119
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics	116
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock	104
What’s the next word in large language models?	104
Machine learning prediction of enzyme optimum pH	103
Combinatorial optimization with physics-inspired graph neural networks	102
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling	101
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin	101
How to break information cocoons	100
A new perspective on the simulation of stochastic problems in fluid mechanics with diffusion models	99
Learning from models beyond fine-tuning	98
Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework	98
Laplace neural operator for solving differential equations	98
Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments	96
Learning function from structure in neuromorphic networks	95
Codon language embeddings provide strong signals for use in protein engineering	93
Collaborative creativity in AI	90
Foundation models in healthcare require rethinking reliability	88
Bridging peptide presentation and T cell recognition with multi-task learning	88
AI reality check	88
Accurate and robust protein sequence design with CarbonDesign	87
Designing a strong test for measuring true common-sense reasoning	87
Life-threatening ventricular arrhythmia detection challenge in implantable cardioverter–defibrillators	84
Seeking a quantum advantage for machine learning	84
A deep learning method for recovering missing signals in transcriptome-wide RNA structure profiles from probing experiments	83
Learning high-level visual representations from a child’s perspective without strong inductive biases	82
The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols	79
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics	79
Image-based generation for molecule design with SketchMol	77
Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer	76
What is in your LLM-based framework?	76
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning	75
Autoregressive neural-network wavefunctions for ab initio quantum chemistry	74
Tandem mass spectrum prediction for small molecules using graph transformers	74
Unifying multi-sample network inference from prior knowledge and omics data with CORNETO	73
A deep generative model enables automated structure elucidation of novel psychoactive substances	72