Alban Bornet
Alban Bornet
UNIGE (Université de Genève)
Verified email at
Cited by
Cited by
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
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
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
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
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
Dissecting (un) crowding
OH Choung, A Bornet, A Doerig, MH Herzog
Journal of vision 21 (10), 10-10, 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
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
Comparing neural language models for medical concept representation and patient trajectory prediction
A Bornet, D Proios, A Yazdani, F Jaume-Santero, G Haller, E Choi, ...
medRxiv, 2023.06. 01.23290824, 2023
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
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
A model with top-down control of the range of perceptual grouping
G Francis, A Bornet
Journal of Vision 19 (10), 151a-151a, 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
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
ProcNet: Deep Predictive Coding Model for Robust-to-occlusion Visual Segmentation and Pose Estimation
M Zechmair, A Bornet, Y Morel
arXiv preprint arXiv:2310.18009, 2023
BioWiC: An Evaluation Benchmark for Biomedical Concept Representation
H Rouhizadeh, I Nikishina, A Yazdani, A Bornet, B Zhang, J Ehrsam, ...
bioRxiv, 2023.11. 08.566170, 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
Global information processing in feedforward deep networks
B Lonnqvist, A Bornet, A Doerig, MH Herzog
Journal of Vision 22 (14), 3212-3212, 2022
(Un) crowding is pre-attentive
Y Markov, A Bornet, N Tiurina, M Herzog
Perception 51, 190, 2022
How crowding challenges (feedforward) convolutional neural networks
B Lonnqvist, A Doerig, A Bornet, G Francis, L Schmittwilken, MH Herzog
Journal of Vision 21 (9), 2039-2039, 2021
The system can't perform the operation now. Try again later.
Articles 1–20