Publications | MALICE

Selected publications

2024

2023

Learning PDE to model self-organization of matter

Eduardo Brandao, Jean-Philippe Colombier, Stefan Duffner, and 6 more authors

Entropy, 2023

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Is My Neural Net Driven by the MDL Principle?

Eduardo Brandao, Stefan Duffner, Rémi Emonet, and 3 more authors

In ECML, 2023

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Predicting Laser-Induced Colors of Random Plasmonic Metasurfaces and Optimizing Image Multiplexing Using Deep Learning

Hongfeng Ma, Nicolas Dalloz, Amaury Habrard, and 5 more authors

ACS Nano, Jun 2023

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Learning Complexity to Guide Light-Induced Self-Organized Nanopatterns

Eduardo Brandao, Anthony Nakhoul, Stefan Duffner, and 7 more authors

Physical Review Letters, May 2023

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Proposal-contrastive pretraining for object detection from fewer data

Quentin Bouniot, Romaric Audigier, Angélique Loesch, and 1 more author

In ICLR, May 2023

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Conditional Variational AutoEncoder based on Stochastic Attacks

Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, and 2 more authors

p-tches, Mar 2023
A general framework for the practical disintegration of PAC-Bayesian bounds

Paul Viallard, Pascal Germain, Amaury Habrard, and 1 more author

Machine Learning, Oct 2023
Deep Stacking Ensemble Learning applied to Profiling Side-Channel Attacks

Dorian Llavata, Eleonora Cagli, Rémi Eyraud, and 2 more authors

In CARDIS, Nov 2023

Exhaustive consolidated list (automatic export)

2024

[Mitarchuk et al. 2024] V. Mitarchuk, C. Lacroce, R. Eyraud, R. Emonet, A. Habrard, G. Rabusseau, Length Independent PAC-Bayes Bounds for Simple RNNs, AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics, Valence, Spain (2024) - CORE Ranking : A
[Viallard et al. 2024] P. Viallard, R. Emonet, A. Habrard, E. Morvant, V. Zantedeschi, Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures, AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain (2024) - CORE Ranking : A
[Robissout et al. 2024] D. Robissout, L. Bossuet, A. Habrard, Scoring the predictions: a way to improve profiling side-channel attacks, Journal of Cryptographic Engineering, (2024) - IF : 1.9 (Q3)
[Bilko et al. 2024] K. Bilko, R. Alía, A. Constantino, A. Coronetti, S. Danzeca, M. Delrieux, N. Emriskova, M. Fraser, S. Girard, E. Johnson, M. Sebban, F. Ravotti, A. Waets, CHARM High-energy Ions for Micro Electronics Reliability Assurance (CHIMERA), IEEE Transactions on Nuclear Science, pp. 1-1 (2024) - IF : 1.8 (Q2)
[Biłko et al. 2024] K. Biłko, R. Alía, M. Barbero, S. Girard, Y. Aguiar, M. Cecchetto, C. Belanger-Champagne, S. Danzeca, W. Hajdas, A. Hands, P. Holgado, Y. Garcia, A. Maestre, D. Prelipcean, F. Ravotti, M. Sebban, Mixed-field Radiation Monitoring and Beam Characterisation Through Silicon Diode Detectors, IEEE Transactions on Nuclear Science, vol. 71(4), pp. 777-784 (2024) - IF : 1.8 (Q2)

2023

[Leteno et al. 2023] T. Leteno, A. Gourru, C. Laclau, R. Emonet, C. Gravier, Fair Text Classification with Wasserstein Independence, 2023 Conference on Empirical Methods in Natural Language Processing, pp. 15790-15803, Singapore, Singapore (2023) - CORE Ranking : A*
[Biłko et al. 2023a] K. Biłko, R. Alía, S. Girard, M. Barbero, M. Cecchetto, C. Belanger-Champagne, M. Brucoli, S. Danzeca, A. Hands, P. Holgado, Y. Garcia, A. Maestre, M. Sebban, M. Widorski, Ultra-large Silicon Diode for Characterising Low-intensity Radiation Environments, IEEE Transactions on Nuclear Science, vol. 71(4), pp. 770-776 (2023) - IF : 1.8 (Q2)
[Llavata et al. 2023] D. Llavata, E. Cagli, R. Eyraud, V. Grosso, L. Bossuet, Deep Stacking Ensemble Learning Applied to Profiling Side-Channel Attacks, Smart Card Research and Advanced Application Conference (CARDIS 2023), pp. 235-255, Amsterdam (NETHERLANDS), Netherlands (2023) - CORE Ranking : C
[Biłko et al. 2023b] K. Biłko, R. Alía, Y. Aguiar, S. Danzeca, D. Francesca, S. Gilardoni, S. Girard, D. Ricci, M. Sebban, S. Uznanski, Radiation environment in the Large Hadron Collider during the 2022 restart and related RHA implications, IEEE Transactions on Nuclear Science, vol. 71(4), pp. 607-617 (2023) - IF : 1.8 (Q2)
[Brandao et al. 2023b] E. Brandao, S. Duffner, R. Emonet, A. Habrard, F. Jacquenet, M. Sebban, Is My Neural Net Driven by the MDL Principle?, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 173-189, Turin, France (2023) - CORE Ranking : A
[Eyraud et al. 2023b] R. Eyraud, D. Lambert, B. Tahri, A. Gaffarov, M. Cabanne, J. Heinz, C. Shibata, TAYSIR Competition: Transformer+rnn: Algorithms to Yield Simple and Interpretable Representations, International Conference on Grammatical Inference, pp. 275-290, Rabat, Morocco (2023)
[Bouniot et al. 2023a] Q. Bouniot, R. Audigier, A. Loesch, A. Habrard, Proposal-contrastive pretraining for object detection from fewer data, ICLR 2023 - The Eleventh International Conference on Learning Representations, pp. https://openreview.net/forum?id=gm0VZ-h-hPy, Kigali, Rwanda (2023) - CORE Ranking : A*
[Brandao et al. 2023a] E. Brandao, A. Nakhoul, S. Duffner, R. Emonet, F. Garrelie, A. Habrard, F. Jacquenet, F. Pigeon, M. Sebban, J. P. Colombier, Learning Complexity to Guide Light-Induced Self-Organized Nanopatterns, Physical Review Letters, vol. 130(), pp. 226201 (2023) - IF : 8.6 (Q1)
[Baksheeva et al. 2023] V. Baksheeva, V. Tiuli, E. Iomdi, S. Petr, O. Filippova, N. Kushnarevich, E. Suleiman, R. Eyraud, F. Devred, M. Serebryakova, N. Shebardina, D. Chistyakov, I. Senin, V. Mitkevich, P. Tsvetkov, E. Zernii, Tear nanoDSF Denaturation Profile Is Predictive of Glaucoma, International Journal of Molecular Sciences, vol. 24(7132), (2023) - IF : 5.6 (Q1)
[Biłko et al. 2023c] K. Biłko, R. Alía, D. Francesca, Y. Aguiar, S. Danzeca, S. Gilardoni, S. Girard, L. Esposito, M. Fraser, G. Mazzola, D. Ricci, M. Sebban, F. Velotti, CERN Super Proton Synchrotron Radiation Environment and Related Radiation Hardness Assurance Implications, IEEE Transactions on Nuclear Science, vol. 70(8), pp. 1606-1615 (2023) - IF : 1.8 (Q2)
[Zaid et al. 2023] G. Zaid, L. Bossuet, M. Carbone, A. Habrard, A. Venelli, Conditional Variational AutoEncoder based on Stochastic Attacks, IACR Transactions on Cryptographic Hardware and Embedded Systems, pp. 310-357 (2023)
[Rußwurm et al. 2023] M. Rußwurm, N. Courty, R. Emonet, S. Lefèvre, D. Tuia, R. Tavenard, End-to-end learned early classification of time series for in-season crop type mapping, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 196(), pp. 445-456 (2023) - IF : 12.7 (Q1)
[Biłko et al. 2023d] K. Biłko, R. Alía, S. Girard, M. Barbero, M. Cecchetto, C. Belanger-Champagne, M. Brucoli, S. Danzeca, A. Hands, P. Holgado, Y. Garcia, A. Maestre, M. Sebban, M. Widorski, Ultra-large Silicon Diode for Characterising Low-intensity Radiation Environments, IEEE Transactions on Nuclear Science, pp. 1-1 (2023) - IF : 1.8 (Q2)
[Bouniot et al. 2023b] Q. Bouniot, A. Loesch, A. Habrard, R. Audigier, Towards few-annotation learning for object detection: are transformer-based models more efficient ?, WACV2023 - 2023 IEEE-CVF Winter Conference on Applications of Computer Vision, pp. 75-84, Waikoloa, HI, United States (2023) - CORE Ranking : A
[Eyraud et al. 2023a] R. Eyraud, S. Ayache, P. Tsvetkov, S. Kalidindi, V. Baksheeva, S. Boissonneau, C. Jiguet-Jiglaire, R. Appay, I. Nanni-Metellus, O. Chinot, F. Devred, E. Tabouret, Plasma nanoDSF Denaturation Profile at Baseline Is Predictive of Glioblastoma EGFR Status, Cancers, (2023) - IF : 5.2 (Q2)
[Viallard et al. 2023] P. Viallard, P. Germain, A. Habrard, E. Morvant, A General Framework for the Practical Disintegration of PAC-Bayesian Bounds, Machine Learning, (2023) - IF : 7.5 (Q1)