| Beyond Bouma's window: How to explain global aspects of crowding? A Doerig, A Bornet, R Rosenholtz, G Francis, AM Clarke, MH Herzog PLoS computational biology 15 (5), e1006580, 2019 | 48 | 2019 |
| Crowding reveals fundamental differences in local vs. global processing in humans and machines A Doerig, A Bornet, OH Choung, MH Herzog Vision research 167, 39-45, 2020 | 40 | 2020 |
| Global and high-level effects in crowding cannot be predicted by either high-dimensional pooling or target cueing A Bornet, OH Choung, A Doerig, D Whitney, MH Herzog, M Manassi Journal of Vision 21 (12), 10-10, 2021 | 19 | 2021 |
| A comparative biology approach to DNN modeling of vision: A focus on differences, not similarities B Lonnqvist, A Bornet, A Doerig, MH Herzog Journal of vision 21 (10), 17-17, 2021 | 19 | 2021 |
| Transformer performance for chemical reactions: Analysis of different predictive and evaluation scenarios F Jaume-Santero, A Bornet, A Valery, N Naderi, D Vicente Alvarez, ... Journal of chemical information and modeling 63 (7), 1914-1924, 2023 | 17 | 2023 |
| Dissecting (un) crowding OH Choung, A Bornet, A Doerig, MH Herzog Journal of Vision 21 (10), 10-10, 2021 | 13 | 2021 |
| Shrinking Bouma’s window: How to model crowding in dense displays A Bornet, A Doerig, MH Herzog, G Francis, E Van der Burg PLoS computational biology 17 (7), e1009187, 2021 | 13 | 2021 |
| Running large-scale simulations on the Neurorobotics Platform to understand vision–the case of visual crowding A Bornet, J Kaiser, A Kroner, E Falotico, A Ambrosano, K Cantero, ... Frontiers in neurorobotics 13, 33, 2019 | 10 | 2019 |
| Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study R Gouareb, A Bornet, D Proios, SG Pereira, D Teodoro Health Data Science 3, 0099, 2023 | 5* | 2023 |
| Comparing neural language models for medical concept representation and patient trajectory prediction A Bornet, D Proios, A Yazdani, FJ Santero, G Haller, E Choi, D Teodoro medRxiv, 2023.06. 01.23290824, 2023 | 5 | 2023 |
| A Dataset for Evaluating Contextualized Representation of Biomedical Concepts in Language Models H Rouhizadeh, I Nikishina, A Yazdani, A Bornet, B Zhang, J Ehrsam, ... Scientific Data 11 (1), 455, 2024 | 4 | 2024 |
| Leveraging patient similarities via graph neural networks to predict phenotypes from temporal data D Proios, A Yazdani, A Bornet, J Ehrsam, I Rekik, D Teodoro 2023 IEEE 10th International Conference on Data Science and Advanced …, 2023 | 3 | 2023 |
| CONORM: Context-Aware Entity Normalization for Adverse Drug Event Detection A Yazdani, H Rouhizadeh, A Bornet, D Teodoro medRxiv, 2023.09. 26.23296150, 2023 | 1 | 2023 |
| Crowding and the importance of grouping and segmentation processes in human vision A Bornet EPFL, 2021 | 1 | 2021 |
| A model with top-down control of the range of perceptual grouping G Francis, A Bornet Journal of Vision 19 (10), 151a-151a, 2019 | 1 | 2019 |
| Shrinking Bouma's window: Visual crowding in dense displays A Bornet, A Doerig, G Francis, MH Herzog, E Van der Burg Perception 48, 27-27, 2019 | 1 | 2019 |
| Crowding asymmetries in a neural model of image segmentation A Bornet, A Doerig, M Herzog, G Francis Journal of Vision 17 (10), 365-365, 2017 | 1 | 2017 |
| A dataset for evaluating clinical research claims in large language models B Zhang, A Bornet, A Yazdani, P Khlebnikov, M Milutinovic, ... Scientific Data 12 (1), 86, 2025 | | 2025 |
| A Scoping Review of Artificial Intelligence Applications in Clinical Trial Risk Assessment D Teodoro, N Naderi, A Yazdani, B Zhang, A Bornet medRxiv, 2025.01. 21.25320310, 2025 | | 2025 |
| Analysis of eligibility criteria clusters based on large language models for clinical trial design A Bornet, P Khlebnikov, F Meer, Q Haas, A Yazdani, B Zhang, P Amini, ... Journal of the American Medical Informatics Association, ocae311, 2024 | | 2024 |
Michael HerzogEPFL, SwitzerlandVerified email at epfl.ch
