Nature Machine Intelligence 2024: all accepted papers
- Augmenting large language models with chemistry tools ↗Andres M Bran, Sam Cox, Oliver Tobias Schilter et al.762 citations
- Leveraging large language models for predictive chemistryKevin Maik Jablonka, Philippe Schwaller, Andres Ortega‐Guerrero et al.367 citations · our summary
- Foundation model for cancer imaging biomarkers ↗Suraj Pai, Dennis Bontempi, Ibrahim Hadžić et al.195 citations
- Generative AI for designing and validating easily synthesizable and structurally novel antibiotics ↗Kyle Swanson, Gary Liu, Denise B. Catacutan et al.184 citations
- Factuality challenges in the era of large language models and opportunities for fact-checkingIsabelle Augenstein, Timothy J. Baldwin, Meeyoung Cha et al.171 citations · our summary
- Machine learning-aided generative molecular design ↗Yuanqi Du, Arian R. Jamasb, Jeff Guo et al.169 citations
- Equivariant 3D-conditional diffusion model for molecular linker design ↗Ilia Igashov, Hannes Stärk, Clément Vignac et al.166 citations
- LLM-based agentic systems in medicine and healthcare ↗Jianing Qiu, Kyle Lam, Guohao Li et al.165 citations
- State-specific protein–ligand complex structure prediction with a multiscale deep generative model ↗Zhuoran Qiao, Weili Nie, Arash Vahdat et al.156 citations
- Laplace neural operator for solving differential equations ↗Qianying Cao, Somdatta Goswami, George Em Karniadakis153 citations
- A transformer-based weakly supervised computational pathology method for clinical-grade diagnosis and molecular marker discovery of gliomas ↗Rui Jiang, Xiaoxu Yin, Pengshuai Yang et al.146 citations
- A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions ↗Yanyi Chu, Dan Yu, Yupeng Li et al.139 citations
- Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves ↗Arvin Tashakori, Zenan Jiang, Amir Servati et al.135 citations
- Predicting equilibrium distributions for molecular systems with deep learning ↗Shuxin Zheng, Jiyan He, Chang Liu et al.134 citations
- Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning ↗Ning Wang, Jiang Bian, Yuchen Li et al.132 citations
- Protein function prediction as approximate semantic entailment ↗Maxat Kulmanov, Francisco J. Guzmán‐Vega, Paula D Duek et al.124 citations
- Autonomous 3D positional control of a magnetic microrobot using reinforcement learning ↗Sarmad Ahmad Abbasi, Awais Ahmed, Seungmin Noh et al.115 citations
- The benefits, risks and bounds of personalizing the alignment of large language models to individuals ↗Hannah Rose Kirk, Bertie Vidgen, Paul Röttger et al.111 citations
- Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations ↗Nick McGreivy, Ammar H. Hakim109 citations
- Physicochemical graph neural network for learning protein–ligand interaction fingerprints from sequence data ↗Huan Yee Koh, Anh T. N. Nguyen, Shirui Pan et al.106 citations
- Guidelines for ethical use and acknowledgement of large language models in academic writing ↗Sebastian Porsdam Mann, Anuraag A Vazirani, Mateo Aboy et al.105 citations
- DNA language model GROVER learns sequence context in the human genome ↗Melissa Sanabria, Jonas Hirsch, Pierre M. Joubert et al.97 citations
- Machine learning for micro- and nanorobots ↗Lidong Yang, Jialin Jiang, Fengtong Ji et al.97 citations
- A neural speech decoding framework leveraging deep learning and speech synthesis ↗Xupeng Chen, Ran Wang, Amirhossein Khalilian-Gourtani et al.95 citations
- Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging ↗Sergios Gatidis, Marcel Früh, Matthias Philipp Fabritius et al.95 citations
- PocketFlow is a data-and-knowledge-driven structure-based molecular generative model ↗Yuanyuan Jiang, Guo Zhang, Jing You et al.94 citations
- Accelerating histopathology workflows with generative AI-based virtually multiplexed tumour profiling ↗Pushpak Pati, Sofia Karkampouna, Francesco Bonollo et al.87 citations
- A large-scale audit of dataset licensing and attribution in AI ↗Shayne Longpre, Robert Mahari, Anthony Chen et al.86 citations
- Multi-animal 3D social pose estimation, identification and behaviour embedding with a few-shot learning framework ↗Yaning Han, Ke Chen, Yunke Wang et al.86 citations
- Codon language embeddings provide strong signals for use in protein engineering ↗Carlos Outeiral, Charlotte Mary Deane78 citations
- A causal perspective on dataset bias in machine learning for medical imaging ↗Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro et al.77 citations
- Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV ↗Aubin Ramon, Montader Ali, Misha Atkinson et al.74 citations
- Efficient and scalable reinforcement learning for large-scale network control ↗Chengdong Ma, Aming Li, Yali Du et al.74 citations
- Machine learning for practical quantum error mitigation ↗Haoran Liao, Derek S. Wang, Iskandar Sitdikov et al.74 citations
- Reconciling privacy and accuracy in AI for medical imaging ↗Alexander Ziller, Tamara T. Mueller, Simon Stieger et al.74 citations
- Tandem mass spectrum prediction for small molecules using graph transformers ↗Adamo Young, Hannes Luc Röst, Bo Wang73 citations
- A soft skin with self-decoupled three-axis force-sensing taxels ↗Youcan Yan, Ahmed Zermane, Jia Pan et al.70 citations
- Invalid SMILES are beneficial rather than detrimental to chemical language models ↗Michael A. Skinnider65 citations
- Lifelike agility and play in quadrupedal robots using reinforcement learning and generative pre-trained models ↗Lei Han, Qingxu Zhu, Jiapeng Sheng et al.65 citations
- Generation of 3D molecules in pockets via a language model ↗Wei Feng, Lvwei Wang, Zaiyun Lin et al.64 citations
- Neural multi-task learning in drug design ↗Stephan Allenspach, Jan A. Hiss, Gisbert Schneider64 citations
- Learning motif-based graphs for drug–drug interaction prediction via local–global self-attention ↗Yi Zhong, Gaozheng Li, Yang Ji et al.63 citations
- Synthetic Lagrangian turbulence by generative diffusion models ↗T. Li, Luca Biferale, Fabio Bonaccorso et al.60 citations
- Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning ↗Marko Njirjak, Lucija Žužić, Marko Babić et al.58 citations
- Evaluating generalizability of artificial intelligence models for molecular datasets ↗Yasha Ektefaie, Andrew Nathanael Shen, Daria Bykova et al.57 citations
- Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions ↗Dong Chen, Jian Liu, Guo‐Wei Wei56 citations
- The dangers of using proprietary LLMs for research ↗Étienne Ollion, Rubing Shen, Ana Macanovic et al.56 citations
- Generic protein–ligand interaction scoring by integrating physical prior knowledge and data augmentation modelling ↗Duanhua Cao, Geng Chen, Jiaxin Jiang et al.55 citations
- Soft robotic shorts improve outdoor walking efficiency in older adults ↗Enrica Tricomi, Francesco Missiroli, Michele Xiloyannis et al.55 citations
- Wing-strain-based flight control of flapping-wing drones through reinforcement learning ↗Taewi Kim, Insic Hong, Sunghoon Im et al.54 citations
- An interpretable RNA foundation model for exploring functional RNA motifs in plants ↗Haopeng Yu, Heng Yang, Wenqing Sun et al.51 citations
- Learning spatiotemporal dynamics with a pretrained generative model ↗Zeyu Li, Han Wang, Yue Zhang et al.50 citations
- A collective AI via lifelong learning and sharing at the edge ↗Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman et al.48 citations
- Contextual feature extraction hierarchies converge in large language models and the brain ↗Gavin Mischler, Yinghao Aaron Li, Stephan Bickel et al.48 citations
- Realistic morphology-preserving generative modelling of the brain ↗Petru-Daniel Tudosiu, Walter Hugo Lopez Pinaya, Pedro F. da Costa et al.46 citations
- On responsible machine learning datasets emphasizing fairness, privacy and regulatory norms with examples in biometrics and healthcare ↗Surbhi Mittal, Kartik Thakral, Richa Singh et al.45 citations
- Poisoning medical knowledge using large language models ↗Junwei Yang, Hanwen Xu, Srbuhi Mirzoyan et al.45 citations
- Challenges and opportunities in translating ethical AI principles into practice for children ↗Ge Wang, Jun Zhao, Max G. Van Kleek et al.42 citations
- Does it matter if empathic AI has no empathy? ↗Garriy Shteynberg, Jodi Halpern, Amir Sadovnik et al.42 citations
- Multimodal language and graph learning of adsorption configuration in catalysis ↗Janghoon Ock, Srivathsan Badrinarayanan, Rishikesh Magar et al.42 citations
- Challenges, evaluation and opportunities for open-world learning ↗Mayank Kejriwal, Eric Kildebeck, Robert J. Steininger et al.41 citations
- Learning high-level visual representations from a child’s perspective without strong inductive biases ↗A. Emin Orhan, Brenden M. Lake41 citations
- Leveraging language model for advanced multiproperty molecular optimization via prompt engineering ↗Zhenxing Wu, Odin Zhang, Xiaorui Wang et al.41 citations
- Machine learning for data-centric epidemic forecasting ↗Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal et al.41 citations
- Coordinate-based neural representations for computational adaptive optics in widefield microscopy ↗Iksung Kang, Qinrong Zhang, Stella X. Yu et al.40 citations
- Molecular set representation learning ↗Maria Boulougouri, Pierre Vandergheynst, Daniel Probst40 citations
- A computational framework for neural network-based variational Monte Carlo with Forward Laplacian ↗Ruichen Li, Haotian Ye, Du Jiang et al.39 citations
- Deep learning for predicting rate-induced tipping ↗Yu Huang, Sebastian Bathiany, Peter Ashwin et al.39 citations
- Interpreting cis-regulatory mechanisms from genomic deep neural networks using surrogate models ↗Evan E. Seitz, David M. McCandlish, Justin B. Kinney et al.39 citations
- Blending neural operators and relaxation methods in PDE numerical solvers ↗Enrui Zhang, Adar Kahana, Alena Kopaničáková et al.38 citations
- Sliding-attention transformer neural architecture for predicting T cell receptor–antigen–human leucocyte antigen binding ↗Ziyan Feng, Jingyang Chen, Youlong Hai et al.38 citations
- Delineating the effective use of self-supervised learning in single-cell genomics ↗Till Richter, Mojtaba Bahrami, Yufan Xia et al.34 citations
- Distributed constrained combinatorial optimization leveraging hypergraph neural networks ↗Nasimeh Heydaribeni, Xinrui Zhan, Ruisi Zhang et al.34 citations
- A call for an industry-led initiative to critically assess machine learning for real-world drug discovery ↗Cas Wognum, Jeremy R. Ash, Matteo Aldeghi et al.32 citations
- Efficient generation of protein pockets with PocketGen ↗Zaixi Zhang, Wan Xiang Shen, Qi Liu et al.32 citations
- General-purpose foundation models for increased autonomy in robot-assisted surgery ↗Samuel Schmidgall, Ji Woong Kim, Alan Kuntz et al.32 citations
- Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock ↗Shihao Feng, Zhen‐Yu Chen, Chengwei Zhang et al.32 citations
- Pre-training with fractional denoising to enhance molecular property prediction ↗Yuyan Ni, Shikun Feng, Xin Hong et al.32 citations
- Quantum circuit synthesis with diffusion models ↗Florian Fürrutter, Gorka Muñoz-Gil, Hans J. Briegel31 citations
- Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology ↗Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar et al.31 citations
- Epitope-anchored contrastive transfer learning for paired CD8+ T cell receptor–antigen recognition ↗Yumeng Zhang, Zhikang Wang, Yunzhe Jiang et al.30 citations
- A bioactivity foundation model using pairwise meta-learning ↗Bin Feng, Zequn Liu, Nan-Lan Huang et al.29 citations
- Accurate and robust protein sequence design with CarbonDesign ↗Milong Ren, Chungong Yu, Dongbo Bu et al.29 citations
- Deep learning prediction of glycopeptide tandem mass spectra powers glycoproteomics ↗裕文 宗, Yuxin Wang, Xipeng Qiu et al.27 citations
- Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion ↗Osama Abdin, Philip M. Kim27 citations
- Federated learning is not a cure-all for data ethics ↗Marieke Bak, Vince I. Madai, Leo Anthony Celi et al.27 citations
- Toward a framework for risk mitigation of potential misuse of artificial intelligence in biomedical research ↗Artem A. Trotsyuk, Quinn Waeiss, Raina Talwar Bhatia et al.27 citations
- Automated construction of cognitive maps with visual predictive coding ↗James Gornet, Matt W. Thomson26 citations
- Weak signal extraction enabled by deep neural network denoising of diffraction data ↗Jens Oppliger, M. Michael Denner, J. Küspert et al.26 citations
- Deeper evaluation of a single-cell foundation model ↗Rebecca Peyser Boiarsky, Nalini Singh, Alejandro Buendia et al.24 citations
- Geometry-enhanced pretraining on interatomic potentials ↗Taoyong Cui, Chenyu Tang, Mao Su et al.24 citations
- Learning integral operators via neural integral equations ↗Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro et al.24 citations
- Systematic analysis of 32,111 AI model cards characterizes documentation practice in AI ↗Weixin Liang, Nazneen Fatema Rajani, Xinyu Yang et al.24 citations
- Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers ↗Harry Coppock, George Nicholson, Ivan Kiskin et al.23 citations
- Maximum diffusion reinforcement learning ↗Thomas A. Berrueta, Allison Pinosky, Todd D. Murphey23 citations
- Stable Cox regression for survival analysis under distribution shifts ↗Shaohua Fan, Renzhe Xu, Qian Dong et al.23 citations
- Development of AI-assisted microscopy frameworks through realistic simulation with pySTED ↗Anthony Bilodeau, Albert Michaud-Gagnon, Julia Chabbert et al.22 citations
- Efficient learning of accurate surrogates for simulations of complex systems ↗A. Diaw, Michael M. McKerns, Irina Sagert et al.22 citations
- Neuromorphic visual scene understanding with resonator networks ↗Alpha Renner, Lazar Supic, Andreea Danielescu et al.21 citations
- A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features ↗Davide Carnevali, Limei Zhong, Esther González-Almela et al.20 citations
This page in Markdown → https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/2024/papers/