Publications
For an updated list, please see my Google Scholar.
Publications
S. Basu, M. A. Legault, A. Romero-Soriano, D. Precup. "On the challenges of using reinforcement learning in precision drug dosing: delay and prolongedness of action effects". AAAI, 2023 (oral). [pdf][BibTex]
E. J. Smith, M. Drozdzal, D. Nowrouzezahrai, D. Meger, A. Romero-Soriano. "Uncertainty-driven active vision for implicit scene reconstruction". arXiv preprint:2210.00978, 2022. [pdf][BibTex]
P. Goyal, A. Romero-Soriano, C. Hazirbas, L. Sagun, N. Usunier. "Fairness Indicators for Systematic Assessments of Visual Feature Extractors". ACM FAccT Conference, 2022. [pdf][BibTex]
T. Bakker, M. J. Muckley, A. Romero-Soriano, M. Drozdzal*, L. Pineda*. "On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction". Medical Imaging with Deep Learning (MIDL) conference, 2022. [pdf][BibTex]
A. Casanova, M. Careil, J. Verbeek, M. Drozdzal*, A. Romero-Soriano*. "Instance-conditioned GAN". Neural Information Processing Systems (NeurIPS), 2021 (spotlight). [pdf][BibTex]
E. J. Smith, D. Meger, L. Pineda, R. Calandra, J. Malik, A. Romero-Soriano*, M. Drozdzal*. "Active 3D shape reconstruction from vision and touch". Neural Information Processing Systems (NeurIPS), 2021. [pdf][BibTex]
B. Knyazev, M. Drozdzal*, G. W. Taylor*, A. Romero-Soriano*. "Parameter prediction for unseen deep architectures". Neural Information Processing Systems (NeurIPS), 2021. [pdf][BibTex]
C. Reddy, D. Sharma, S. Mehri, A. Romero-Soriano, S. Shabanian*, S. Honari*. "Benchmarking bias mitigation algorithms in representation learning through fairness metrics". Neural Information Processing Systems (NeurIPS), 2021. [pdf][BibTex]
L. Ma, R. Rabbany, A. Romero-Soriano. "Graph Attention Networks with Positional Embeddings". Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021. [pdf][BibTex]
A. Casanova, M. Drozdzal, A. Romero-Soriano. "Generating unseen complex scenes: are we there yet?" arXiv preprint:2012.04027, 2020. [pdf][BibTex].
E. J. Smith, R. Calandra, A. Romero, G. Gkioxari, D. Meger, J. Malik, M. Drozdzal. "3D Shape Reconstruction from Vision and Touch". Neural Information Processing Systems (NeurIPS), 2020. [pdf][BibTex]
L. Pineda, S. Basu, A. Romero, R. Calandra, M. Drozdzal. "Active MR k-space Sampling with Reinforcement Learning". International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020. [pdf][BibTex]
L. Sagun, C. Gulcehre, A. Romero, N. Rostemzadeh, S. Sarao Mannelli. "Post-Workshop Report on, Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver". arXiv preprint arXiv:2007.13483, 2020. [pdf][BibTex]
K. Wagstyl, S. Larocque, G. Cucurull, C. Lepage, J. P. Cohen, S. Bludau, N. Palomero-Gallagher, L. B. Lewis, T. Funck, H. Spitzer, T. Dickscheid, P. C. Fletcher, A. Romero, K. Zilles, K. Amunts, Y. Bengio, A. C. Evans. "BigBrain 3D atlas of cortical layers: cortical and laminar thickness gradients diverge in sensory and motor cortices". PLOS Biology 18 (4), e3000678, 2020. [link]
T. DeVries, A. Romero, L. Pineda, G. W. Taylor, M. Drozdzal. "On the Evaluation of Conditional GANs". preprint arXiv:1907.08175, 2019. [pdf][BibTex]
L. Pineda*, A. Salvador*, M. Drozdzal, A. Romero. "Elucidating image-to-set prediction: An analysis of models, losses and datasets". preprint arXiv:1904.05709, 2019. [pdf] [BibTex]
E. J. Smith, S. Fujimoto, A. Romero, D. Meger. "GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects". International Conference on Machine Learning (ICML), 2019. [pdf] [BibTex] [code]
S. Basu, K. Wagstyl, A. Zandifar, L. Collins, A. Romero, D. Precup. "Early Prediction of Alzheimer’s Disease Progression Using Variational Autoencoders". International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. [pdf][BibTex]
K. Wagstyl, S. Larocque, G. Cucurull, C. Lepage, J. P. Cohen, S. Bludau, N. Palomero-Gallagher, T. Funck, H. Spitzer, T. Dicksheid, P. C. Fletcher, A. Romero, K. Zilles, K. Amunts, Y. Bengio, A. C. Evans. "Automated segmentation of cortical layers in BigBrain reveals divergent cortical and laminar thickness gradients in sensory and motor cortices". preprint bioRxiv:580597, 2019. [pdf]
A. Salvador, M. Drozdzal, X. Giro-i-Nieto, A. Romero. “Inverse Cooking: Recipe Generation from Food Images". Computer Vision and Pattern Recognition (CVPR), 2019. [pdf] [BibTex]
Z. Zhang, A. Romero, M. J. Muckley, P. Vincent, L. Yang, M. Drozdzal. "Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition". Computer Vision and Pattern Recognition (CVPR), 2019. [pdf] [BibTex]
Z. Zhang, A. Romero, M. J. Muckley, P. Vincent, L. Yang, M. Drozdzal. "Active Acquisition for MRI Reconstruction". International Society for Magnetic Resonance in Medicine (ISMRM), 2019. [abstract]
G. Cucurull, K. Wagstyl, A. Casanova, P. Veličković, E. Jakobsen, M. Drozdzal, A. Romero, A. Evans and Y. Bengio. “Convolutional neural networks for mesh-based parcellation of the cerebral cortex”. Medical Imaging with Deep Learning (MIDL) conference, 2018. [pdf] [BibTex]
A. Casanova, G. Cucurull, M. Drozdzal, A. Romero and Y. Bengio. “On the iterative refinement of densely connected representation levels for semantic segmentation”. Workshop on Autonomous Driving, CVPR, 2018. [pdf] [BibTex] [code]
P. Veličković, G. Cucurull, A. Casanova, A. Romero, P. Liò and Y. Bengio. “Graph Attention Networks”. International Conference on Representation Learning (ICLR), 2018. [pdf] [BibTex] [code]
G. Cucurull, K. Wagstyl, A. Casanova, P. Veličković, E. Jakobsen, A. Romero, A. Evans, Y. Bengio. "Graph Convolutional Neural Networks for Cortical Mesh Segmentation". BigNeuro Workshop @ NIPS, 2017.
A. Romero, M. Drozdzal, A. Erraqabi, S. Jégou and Y. Bengio. “Image Segmentation by Iterative Inference from Conditional Score Estimation”. preprint arXiv:1705.07450, 2017. [pdf] [BibTex] [code]
M. Drozdzal, G. Chartrand, E. Vorontsov, L. Di Jorio, A. Tang, A. Romero, Y. Bengio, C. Pal and S. Kadoury. “Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation”. Medical Image Analysis, 2017. [pdf] [BibTex]
A. Romero, P.L. Carrier, A. Erraqabi, T. Sylvain, A. Auvolat, E. Dejoie, M.A. Legault, M.P. Dubé, J.G. Hussin and Y. Bengio. “Diet Networks: Thin Parameters for Fat Genomics”. International Conference on Representation Learning (ICLR), 2017. [pdf] [BibTex] [code]
S. Jégou, M. Drozdzal, D. Vázquez, A. Romero and Y. Bengio. “The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation”. Workshop on Computer Vision in Vehicle Technology CVPR, 2017. Best paper award. [pdf] [BibTex] [code]
D. Vázquez, J. Bernal, F. J. Sánchez, G. Fernández-Esparrach, A. M. López, A. Romero, M. Drozdzal and A. Courville. “A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images”. Journal of Healthcare Engineering, 2017. [pdf] [BibTex]
F. Visin, M. Ciccone, A. Romero, K. Kastner, K. Cho, Y. Bengio, M. Matteucci and A. Courville. “ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation”. Deep-vision workshop CVPR, 2016. Best paper award. [pdf] [BibTex] [code]
M. Campos-Taberner, A. Romero-Soriano, C. Gatta, G. Camps-Valls, A. Lagrange, B. Le Saux, A. Beaupere, A. Boulch, A. Chan-Hon-Tong, S. Herbin, H. Randrianarivo, M. Ferecatu, M. Shimoni, G. Moser and D. Tuia. “Processing of Extremely High-Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest–Part A: 2-D Contest”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016. [pdf] [BibTex]
A. Romero, C. Gatta and G. Camps-Valls. “Unsupervised Deep Feature Extraction for Remote Sensing Image Classification”. IEEE Transactions on Geoscience and Remote Sensing, 2016. [pdf] [BibTex]
A. Romero, N. Ballas, S. Ebrahimi Kahou, A. Chassang, C. Gatta and Y. Bengio, “FitNets: Hints for Thin Deep Nets”. International Conference on Representation Learning (ICLR), 2015. [pdf] [BibTex] [code]
A. Romero, P. Radeva and C. Gatta. “Meta-parameter free unsupervised sparse feature learning”. IEEE Pattern Analysis and Machine Intelligence, 2015. [pdf] [BibTex] [project page]
M. Campos-Taberner, A. Romero, C. Gatta and G. Camps-Valls, “Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination”. IEEE International Geoscience and Remote Sensing Symposium, 2015. Winner (ranked 1st) of the 2D Contest of the 2015 IEEE GRSS Data Fusion Contest. [pdf] [BibTex]
A. Romero, C. Gatta and G. Camps-Valls. “Unsupervised Deep Feature Extraction Of Hyperspectral Images”. IEEE Workshop on Hyperspectral Image and Signal Processing". WHISPERS, 2014. [pdf] [BibTex]
C. Gatta, A. Romero and J. van de Weijer. “Unrolling loopy top-down semantic feedback in convolutional deep networks”. Deep-vision workshop CVPR, 2014. [pdf] [BibTex]
A. Romero and C. Gatta, “Do we really need all these neurons?”. Iberian Conference on Pattern Recognition and Image Analysis, 2013. [pdf] [BibTex]
A. Romero, S. Petkov, C. Gatta, Dr. M. Sabaté and P. Radeva, “Efficient Automatic Segmentation of Vessels”. Medical Image Understanding and Analysis 2012. [pdf] [BibTex]
S. Petkov, A. Romero, X. Carrillo Suarez, P. Radeva and C. Gatta, “Robust and accurate diaphragm border detection in cardiac X-Ray angiographies”. STACOM Workshop, MICCAI, 2012. [pdf] [BibTex]
E. Serradell, A. Romero, R. Leta, C. Gatta, and F. Moreno-Noguer , “Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-ray Images”. International Conference on Computer Vision, 2011. [pdf] [BibTex]