Advances in neural information processing systems 7

Reliable machine learning models in genomic medicine using conformal prediction

Papangelou, C., Kyriakidis, K., Natsiavas, P., Chouvarda, I., & Malousi, A. (2025) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2025.1507448 · Cited by 12

Distinct brain morphometry patterns revealed by deep learning improve prediction of post-stroke aphasia severity

Teghipco, A., Newman-Norlund, R., Fridriksson, J., Rorden, C., & Bonilha, L. (2024) · Communications Medicine · doi:10.1038/s43856-024-00541-8 · Cited by 11

Neural networks memorise personal information from one sample

Hartley, J., Sanchez, P. P., Haider, F., & Tsaftaris, S. A. (2023) · Scientific Reports · doi:10.1038/s41598-023-48034-3 · Cited by 10

REVEL Framework to Measure Local Linear Explanations for Black‐Box Models: Deep Learning Image Classification Case Study

Sevillano-García, I., Luengo, J., & Herrera, F. (2023) · International Journal of Intelligent Systems · doi:10.1155/2023/8068569 · Cited by 10

An artificial neural network model to predict structure-based protein–protein free energy of binding from Rosetta-calculated properties

Ferraz, M. V. F., Neto, J. C. S., Lins, R. D., & Teixeira, E. S. (2023) · Physical Chemistry Chemical Physics · doi:10.1039/d2cp05644e · Cited by 9

High-resolution real-space reconstruction of cryo-EM structures using a neural field network

Huang, Y., Zhu, C., Yang, X., & Liu, M. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00870-2 · Cited by 9

Generating Meaning: Active Inference and the Scope and Limits of Passive AI

Pezzulo, G., Parr, T., Cisek, P., Clark, A., & Friston, K. (2023) · doi:10.31234/osf.io/8xgzv · Cited by 8

AI-Powered Game Design: Experts Employing ChatGPT in the Game Design Process

LANKES, M., & STOCKL, A. (2023) · The Eurasia Proceedings of Science Technology Engineering and Mathematics · doi:10.55549/epstem.1406194 · Cited by 8

Can You Hear Me Now? Sensitive Comparisons of Human and Machine Perception

Lepori, M. A., & Firestone, C. (2022) · Cognitive Science · doi:10.1111/cogs.13191 · Cited by 7

DeepFeatureX Net: Deep Features eXtractors Based Network for Discriminating Synthetic from Real Images

Pontorno, O., Guarnera, L., & Battiato, S. (2025) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-78305-0_12 · Cited by 6

Ethical and Socially-Aware Data Labels

Beretta, E., Vetrò, A., Lepri, B., & De Martin, J. C. (2019) · Communications in Computer and Information Science · doi:10.1007/978-3-030-11680-4_30 · Cited by 6

Emergence of Collaborative Hunting via Multi-Agent Deep Reinforcement Learning

Tsutsui, K., Takeda, K., & Fujii, K. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-37660-3_15 · Cited by 5

Amnesiac Machine Learning

Graves, L., Nagisetty, V., & Ganesh, V. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i13.17371 · Cited by 5

Artificial neural network encoding of molecular wavefunctions for quantum computing

Hagai, M., Sugiyama, M., Tsuda, K., & Yanai, T. (2023) · Digital Discovery · doi:10.1039/d2dd00093h · Cited by 5

Exploring the Structural Diversity and Evolution of the D1 Subunit of Photosystem II Using AlphaFold and Foldtree

Kim, T. D., Pretorius, D., Murray, J. W., & Cardona, T. (2025) · Physiologia Plantarum · doi:10.1111/ppl.70284 · Cited by 4

EGGNet, a Generalizable Geometric Deep Learning Framework for Protein Complex Pose Scoring

Wang, Z., Brand, R., Adolf-Bryfogle, J., Grewal, J., Qi, Y., Combs, S. A., Golovach, N., Alford, R., Rangwala, H., & Clark, P. M. (2024) · ACS Omega · doi:10.1021/acsomega.3c04889 · Cited by 3

Utilizing Data Imbalance to Enhance Compound–Protein Interaction Prediction Models

(2025) · doi:10.1002/aisy.202400985 · Cited by 3

Using Deep Graph Neural Networks Improves Physics-Based Hydration Free Energy Predictions Even for Molecules Outside of the Training Set Distribution

Elder, L. H., & Onufriev, A. V. (2025) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5c02263 · Cited by 2

MuST: Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction

Miao, Y., & Yu, L. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-47425-5_25 · Cited by 1

CysPresso: A classification model utilizing deep learning protein representations to predict recombinant expression of cysteine-dense peptides

Ouellet, S., Ferguson, L., Lau, A. Z., & Lim, T. K. Y. (2022) · doi:10.1101/2022.09.17.508377