La recherche joue un rôle majeur dans le domaine du Machine Learning. Avec des publications de premier ordre chaque année, l’EPFL jouit d’une excellente réputation.


Visual question answering from another perspective: CLEVR mental rotation tests *

C. Beckham; M. Weiss; F. Golemo; S. Honari; D. Nowrouzezahrai et al. 

Pattern Recognition. 2023-04-01. Vol. 136, p. 109209. DOI : 10.1016/j.patcog.2022.109209.

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

V. Swamy; S. Du; M. Marras; T. Käser 

2023-03-13. LAK 2023: The 13th International Learning Analytics and Knowledge Conference, Arlington, Texas, USA, March 13-17, 2023. DOI : 10.1145/3576050.3576147.

End-to-end learned early classification of time series for in-season crop type mapping

M. Rußwurm; N. Courty; R. Emonet; S. Lefèvre; D. Tuia et al. 

ISPRS Journal of Photogrammetry and Remote Sensing. 2023-01-25. Vol. 196, p. 445-456. DOI : 10.1016/j.isprsjprs.2022.12.016.

Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts

A. Levering; D. Marcos; J. van Vliet; D. Tuia 

Remote Sensing of Environment. 2023-01-25. Vol. 287, p. 113454. DOI : 10.1016/j.rse.2023.113454.

Single-Molecule Peptide Identification Using Fluorescence Blinking Fingerprints

S. Puntener; P. Rivera-Fuentes 

Journal Of The American Chemical Society. 2023-01-05. DOI : 10.1021/jacs.2c12561.

Deep Learning for Localized-Haptic Feedback in Tactile Surfaces

C. Hernandez Mejia / Y. Perriard (Dir.)  

Lausanne, EPFL, 2023. 

Sparse Autoencoders for Speech Modeling and Recognition

S. H. Kabil / H. Bourlard (Dir.)  

Lausanne, EPFL, 2023. 

De novo designed proteins: a study in engineering novel folds and functions

A. K. Van Hall-Beauvais / B. E. Ferreira De Sousa Correia (Dir.)  

Lausanne, EPFL, 2023. 

Solving Non-linear Kolmogorov Equations in Large Dimensions by Using Deep Learning: A Numerical Comparison of Discretization Schemes

R. Marino; N. Macris 

Journal Of Scientific Computing. 2023-01-01. Vol. 94, num. 1, p. 8. DOI : 10.1007/s10915-022-02044-x.

Brain microstructural and functional MRI: developments and application to a rat model of Alzheimer’s disease

Y. Diao / R. Gruetter; I. O. Jelescu (Dir.)  

Lausanne, EPFL, 2023. 

cgNA+: A sequence-dependent coarse-grain model of double-stranded nucleic acids

R. Sharma / J. Maddocks (Dir.)  

Lausanne, EPFL, 2023. 

Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors

T. Riedlinger; M. Rottmann; M. Schubert; H. Gottschalk 

2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA, January 3-7, 2023.

Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification

M. Rottmann; M. Reese 

2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA, January 3-7, 2023.


RayTran: 3D Pose Estimation and Shape Reconstruction of Multiple Objects from Videos with Ray-Traced Transformers

M. J. Tyszkiewicz; K-K. Maninis; S. Popov; V. Ferrari 

2022-12-12. European Conference on Computer Vision, Tel-Aviv, Israel, October 23-27, 2022. p. 211-228. DOI : 10.1007/978-3-031-20080-9_13.

ALPINE: Analog In-Memory Acceleration with Tight Processor Integration for Deep Learning

J. A. H. Klein; I. Boybat; Y. M. Qureshi; M. Dazzi; A. S. J. Levisse et al. 

IEEE Transactions on Computers (TC). 2022-12-09. DOI : 10.1109/TC.2022.3230285.

Time-encoded multiplication-free spiking neural networks: application to data classification tasks

A. Stanojevic; G. Cherubini; S. Wozniak; E. Eleftheriou 

Neural Computing & Applications. 2022-12-05. DOI : 10.1007/s00521-022-07910-1.

Fine-grained population mapping from coarse census counts and open geodata

N. Metzger; J. E. Vargas-Muñoz; R. C. Daudt; B. Kellenberger; T. T-T. Whelan et al. 

Scientific Reports. 2022-12-01. Vol. 12, num. 1. DOI : 10.1038/s41598-022-24495-w.

Machine-learning accelerated identification of exfoliable two-dimensional materials

M. Tohidi Vahdat; K. Varoon Agrawal; G. Pizzi 

Machine Learning-Science And Technology. 2022-12-01. Vol. 3, num. 4, p. 045014. DOI : 10.1088/2632-2153/ac9bca.

Modeling Object Dissimilarity for Deep Saliency Prediction

B. Aydemir; D. Bhattacharjee; T. Zhang; S. Kim; M. Salzmann et al. 

Transactions on Machine Learning Research. 2022-11-24. 

Deep learning-based galaxy image deconvolution

U. Akhaury; J-L. Starck; P. Jablonka; F. Courbin; K. Michalewicz 

Frontiers In Astronomy And Space Sciences. 2022-11-18. Vol. 9, p. 1001043. DOI : 10.3389/fspas.2022.1001043.

Assessment of idiopathic inflammatory myopathy using a deep learning method for muscle T2 mapping segmentation

F. Wang; S. Zhou; B. Hou; F. Santini; L. Yuan et al. 

European Radiology. 2022-11-18. DOI : 10.1007/s00330-022-09254-9.

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

J. Sauder; M. Genzel; P. Jung 

IEEE Journal on Selected Areas in Information Theory. 2022-11-11.  p. 1-1. DOI : 10.1109/JSAIT.2022.3221644.

Generalization of an Encoder-Decoder LSTM model for flood prediction in ungauged catchments

Y. Zhang; S. Ragettli; P. Molnar; O. Fink; N. Peleg 

Journal Of Hydrology. 2022-11-01. Vol. 614, p. 128577. DOI : 10.1016/j.jhydrol.2022.128577.

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios*

A. Favero; F. Cagnetta; M. Wyart 

Journal Of Statistical Mechanics-Theory And Experiment. 2022-11-01. Vol. 2022, num. 11, p. 114012. DOI : 10.1088/1742-5468/ac98ab.

Relative stability toward diffeomorphisms indicates performance in deep nets

L. Petrini; A. Favero; M. Geiger; M. Wyart 

Journal Of Statistical Mechanics-Theory And Experiment. 2022-11-01. Vol. 2022, num. 11, p. 114013. DOI : 10.1088/1742-5468/ac98ac.

Artificial Intelligence Based Methods for Smart and Sustainable Urban Planning: A Systematic Survey

S. C. K. Tekouabou; E. B. Diop; R. Azmi; J. Chenal 

Archives Of Computational Methods In Engineering. 2022-11-01. DOI : 10.1007/s11831-022-09844-2.

CovNet: Covariance networks for functional data on multidimensional domains

S. Sarkar; V. M. Panaretos 

Journal Of The Royal Statistical Society Series B-Statistical Methodology. 2022-10-31. DOI : 10.1111/rssb.12551.

High Resolution Interferometric Imaging of Liquid-Solid Interfaces with HOTNNET

R. Kaviani; J. M. Kolinski 

Experimental Mechanics. 2022-10-28. DOI : 10.1007/s11340-022-00912-z.

Annotation of spatially resolved single-cell data with STELLAR

M. Brbić; K. Cao; J. W. Hickey; Y. Tan; M. P. Snyder et al. 

Nature Methods. 2022-10-24. Vol. 19, num. 11, p. 1411-1418. DOI : 10.1038/s41592-022-01651-8.

Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence

G. Starke; M. Ienca 

Cambridge Quarterly Of Healthcare Ethics. 2022-10-20.  p. PII S0963180122000445. DOI : 10.1017/S0963180122000445.

On combining denoising with learning-based image decoding

L. Larigauderie; M. Testolina; T. Ebrahimi 

2022-10-03. Applications of Digital Image Processing XLV, San Diego, August, 2022. DOI : 10.1117/12.2636682.

A novel assessment framework for learning-based deepfake detectors in realistic conditions

Y. Lu; T. Ebrahimi 

2022-10-03. SPIE Optical Engineering + Applications, San Diego, California, USA, August 21-25, 2022. p. 23. DOI : 10.1117/12.2636683.

Improved spiking neural network for intershaft bearing fault diagnosis

J. Wang; T. Li; C. Sun; R. Yan; X. Chen 

Journal Of Manufacturing Systems. 2022-10-01. Vol. 65, p. 208-219. DOI : 10.1016/j.jmsy.2022.09.003.

CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion

G. Bellegarda; A. Ijspeert 

Ieee Robotics And Automation Letters. 2022-10-01. Vol. 7, num. 4, p. 12547-12554. DOI : 10.1109/LRA.2022.3218167.

Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and operando X-ray radiography guidance

V. Pandiyan; G. Masinelli; N. Claire; Tri Le-Quang; M. Hamidi-Nasab et al. 

Additive Manufacturing. 2022-10-01. Vol. 58, p. 103007. DOI : 10.1016/j.addma.2022.103007.

Roadmap on wavefront shaping and deep imaging in complex media

S. Gigan; O. Katz; H. B. de Aguiar; E. R. Andresen; A. Aubry et al. 

Journal Of Physics-Photonics. 2022-10-01. Vol. 4, num. 4, p. 042501. DOI : 10.1088/2515-7647/ac76f9.

In vivo magnetic resonance P-31-Spectral Analysis With Neural Networks: 31P-SPAWNN

J. Songeon; S. Courvoisier; L. Xin; T. Agius; O. Dabrowski et al. 

Magnetic Resonance In Medicine. 2022-09-25. DOI : 10.1002/mrm.29446.

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

A. Amirshahi; A. Thomas; A. Aminifar; T. Rosing; D. Atienza Alonso 

IEEE Journal of Biomedical and Health Informatics (JBHI). 2022-09-22. DOI : 10.1109/jbhi.2022.3208780.

On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation

S. K. Roy; L. Citraro; S. Honari; P. Fua 

2022-09-12. 10th International Conference on 3D Vision 2022 (3DV), Prague, Czechia, September 12-15, 2022.

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

T-A. Nguyen; B. Kellenberger; D. Tuia 

Remote Sensing of Environment. 2022-09-02. Vol. 281, p. 113217. DOI : 10.1016/j.rse.2022.113217.

WikiArtVectors: Style and Color Representations of Artworks for Cultural Analysis via Information Theoretic Measures

B. S. Desikan; H. Shimao; H. Miton 

Entropy. 2022-09-01. Vol. 24, num. 9, p. 1175. DOI : 10.3390/e24091175.

Auto-tuning deep forest for shear stiffness prediction of headed stud connectors

X. Wang; H. Liu; Y. Liu 

Structures. 2022-09-01. Vol. 43, p. 1463-1477. DOI : 10.1016/j.istruc.2022.07.054.

Generating LOD3 building models from structure-from-motion and semantic segmentation

B. G. Pantoja-Rosero; R. Achanta; M. Kozinski; P. Fua; F. Perez-Cruz et al. 

Automation In Construction. 2022-09-01. Vol. 141, p. 104430. DOI : 10.1016/j.autcon.2022.104430.

Karl Jaspers and artificial neural nets: on the relation of explaining and understanding artificial intelligence in medicine

G. Starke; C. Poppe 

Ethics And Information Technology. 2022-09-01. Vol. 24, num. 3, p. 26. DOI : 10.1007/s10676-022-09650-1.

Time-delay estimation in unresolved lensed quasars

L. Biggio; A. Domi; S. Tosi; G. Vernardos; D. Ricci et al. 

Monthly Notices Of The Royal Astronomical Society. 2022-08-19. Vol. 515, num. 4, p. 5665-5672. DOI : 10.1093/mnras/stac2034.

Multiscale light-sheet organoid imaging framework

G. de Medeiros; R. Ortiz; P. Strnad; A. Boni; F. Moos et al. 

Nature Communications. 2022-08-18. Vol. 13, num. 1, p. 4864. DOI : 10.1038/s41467-022-32465-z.

TOPO-Loss for continuity-preserving crack detection using deep learning

B. G. Pantoja-Rosero; D. Oner; M. Kozinski; R. Achanta; P. Fua et al. 

Construction And Building Materials. 2022-08-15. Vol. 344, p. 128264. DOI : 10.1016/j.conbuildmat.2022.128264.

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

B. Denizdurduran; H. Markram; M-O. Gewaltig 

Biological Cybernetics. 2022-08-11. DOI : 10.1007/s00422-022-00940-x.

Deep learning approaches for conformational flexibility and switching properties in protein design

L. S. P. Rudden; M. Hijazi; P. Barth 

Frontiers in Molecular Biosciences. 2022-08-10. Vol. 9, p. 928534. DOI : 10.3389/fmolb.2022.928534.

Review Of Particle Physics

R. L. Workman; V. D. Burkert; V. Crede; E. Klempt; U. Thoma et al. 

Progress Of Theoretical And Experimental Physics. 2022-08-08. Vol. 2022, num. 8, p. 083C01. DOI : 10.1093/ptep/ptac097.

On the robustness of randomized classifiers to adversarial examples

R. Pinot; L. Meunier; F. Yger; C. Gouy-Pailler; Y. Chevaleyre et al. 

Machine Learning. 2022-08-02. DOI : 10.1007/s10994-022-06216-6.

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

S. Choudhury; M. Moret; P. Salvy; D. Weilandt; V. Hatzimanikatis et al. 

Nature Machine Intelligence. 2022-08-01. Vol. 4, num. 8, p. 710-719. DOI : 10.1038/s42256-022-00519-y.

A Compressor Off-Line Washing Schedule Optimization Method With a LSTM Deep Learning Model Predicting the Fouling Trend

J. Chen; X. Tang; J. Lu; H. Zhang 

Journal Of Engineering For Gas Turbines And Power-Transactions Of The Asme. 2022-08-01. Vol. 144, num. 8, p. 081005. DOI : 10.1115/1.4054748.

A prescriptive Dirichlet power allocation policy with deep reinforcement learning

Y. Tian; M. Han; C. Kulkarni; O. Fink 

Reliability Engineering & System Safety. 2022-08-01. Vol. 224, p. 108529. DOI : 10.1016/j.ress.2022.108529.

Scaffolding protein functional sites using deep learning

J. Wang; S. Lisanza; D. Juergens; D. Tischer; J. L. Watson et al. 

Science. 2022-07-22. Vol. 377, num. 6604, p. 387-394. DOI : 10.1126/science.abn2100.

Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineate

D. Oner; M. Kozinski; L. Citraro; P. Fua 

IEEE Transactions on Medical Imaging. 2022-07-21. Vol. 41, num. 12, p. 3675-3685. DOI : 10.1109/TMI.2022.3193072.

GANs for All: Supporting Fun and Intuitive Exploration of GAN Latent Spaces

W. Jiang; R. L. Davis; K. G. Kim; P. Dillenbourg 

2022-07-20. NeurIPS 2021 Competitions and Demonstrations Track, Online , December 6-14, 2022. p. 292-296.

ShapeNet: Shape constraint for galaxy image deconvolution

F. Nammour; U. Akhaury; J. N. Girard; F. Lanusse; F. Sureau et al. 

Astronomy & Astrophysics. 2022-07-19. Vol. 663, p. A69. DOI : 10.1051/0004-6361/202142626.

Combining computational fluid dynamics and neural networks to characterize microclimate extremes: Learning the complex interactions between meso-climate and urban morphology

K. Javanroodi; V. M. Nik; M. G. Giometto; J-L. Scartezzini 

Science Of The Total Environment. 2022-07-10. Vol. 829, p. 154223. DOI : 10.1016/j.scitotenv.2022.154223.

Searching for visual patterns in a children’s drawings collection

R. Annapureddy 


Depth Estimation for Egocentric Rehabilitation Monitoring Using Deep Learning Algorithms

Y. Izadmehr; H. F. Satizabal; K. Aminian; A. Perez-Uribe 

Applied Sciences-Basel. 2022-07-01. Vol. 12, num. 13, p. 6578. DOI : 10.3390/app12136578.

Robust Classification Using Contractive Hamiltonian Neural ODEs

M. Zakwan; L. Xu; G. Ferrari-Trecate 

Ieee Control Systems Letters. 2022-06-28. Vol. 7, p. 145-150. DOI : 10.1109/LCSYS.2022.3186959.

Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks

J. Liu; J. Lan; X. He 

Journal Of Physical Chemistry A. 2022-06-23. Vol. 126, num. 24, p. 3926-3936. DOI : 10.1021/acs.jpca.2c00601.

Autoencoders reloaded

H. Bourlard; S. H. Kabil 

Biological Cybernetics. 2022-06-21. DOI : 10.1007/s00422-022-00937-6.

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

L. Gonzalez-Carabarin; I. A. M. Huijben; B. Veeling; A. Schmid; R. J. G. van Sloun 

Ieee Transactions On Neural Networks And Learning Systems. 2022-06-08. DOI : 10.1109/TNNLS.2022.3176809.

Roadmap on Machine learning in electronic structure

H. J. Kulik; T. Hammerschmidt; J. Schmidt; S. Botti; M. A. L. Marques et al. 

Electronic Structure. 2022-06-01. Vol. 4, num. 2, p. 023004. DOI : 10.1088/2516-1075/ac572f.

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

R. Tenderini; S. Pagani; A. Quarteroni; S. Deparis 

SIAM Journal on Scientific Computing. 2022-06-01. Vol. 44, num. 3, p. B605-B639. DOI : 10.1137/21M1438529.

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

A. Gratsea; P. Huembeli 

Quantum Machine Intelligence. 2022-06-01. Vol. 4, num. 1, p. 2. DOI : 10.1007/s42484-021-00058-6.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

H. Lajous; C. W. Roy; T. Hilbert; P. de Dumast; S. Tourbier et al. 

Scientific Reports. 2022-05-23. Vol. 12, num. 1, p. 8682. DOI : 10.1038/s41598-022-10335-4.

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

N. Frank; D. Lazzarotto; T. Ebrahimi 

2022-05-22. IEEE International Conference on Acoustics, Speech and Signal Processing, Singapore, May 22-27, 2022. p. 4878-4882. DOI : 10.1109/ICASSP43922.2022.9747496.

Deep learning exotic hadrons

L. Ng; L. Bibrzycki; J. Nys; C. Fernandez-Ramirez; A. Pilloni et al. 

Physical Review D. 2022-05-17. Vol. 105, num. 9, p. L091501. DOI : 10.1103/PhysRevD.105.L091501.

Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement

A. Momeni; R. Fleury 

Nature Communications. 2022-05-12. Vol. 13, num. 2651, p. 1-11. DOI : 10.1038/s41467-022-30297-5.

The Food Recognition Benchmark: Using Deep Learning to Recognize Food in Images

S. P. Mohanty; G. Singhal; E. A. Scuccimarra; D. Kebaili; H. Heritier et al. 

Frontiers In Nutrition. 2022-05-06. Vol. 9, p. 875143. DOI : 10.3389/fnut.2022.875143.

Finding quadruply imaged quasars with machine learning – I. Methods

A. Akhazhanov; A. More; A. Amini; C. Hazlett; T. Treu et al. 

Monthly Notices Of The Royal Astronomical Society. 2022-05-05. Vol. 513, num. 2, p. 2407-2421. DOI : 10.1093/mnras/stac925.

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

S. Batzner; A. Musaelian; L. Sun; M. Geiger; J. P. Mailoa et al. 

Nature Communications. 2022-05-04. Vol. 13, num. 1, p. 2453. DOI : 10.1038/s41467-022-29939-5.

Predicting chemical hazard across taxa through machine learning

J. Wu; S. D’Ambrosi; L. Ammann; J. Stadnicka-Michalak; K. Schirmer et al. 

Environment International. 2022-05-01. Vol. 163, p. 107184. DOI : 10.1016/j.envint.2022.107184.

Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process

V. Pandiyan; R. Drissi-Daoudi; S. Shevchik; G. Masinelli; Tri Le-Quang et al. 

Journal Of Materials Processing Technology. 2022-05-01. Vol. 303, p. 117531. DOI : 10.1016/j.jmatprotec.2022.117531.

An occupant-centric control framework for balancing comfort, energy use and hygiene in hot water systems: A model-free reinforcement learning approach

A. Heidari; F. Marechal; D. Khovalyg 

Applied Energy. 2022-04-15. Vol. 312, p. 118833. DOI : 10.1016/j.apenergy.2022.118833.

CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging

D. Perdios; M. Vonlanthen; F. Martinez; M. Arditi; J-P. Thiran 

Ieee Transactions On Ultrasonics Ferroelectrics And Frequency Control. 2022-04-01. Vol. 69, num. 4, p. 1154-1168. DOI : 10.1109/TUFFC.2021.3131383.

Impact and implications of mixed plaque class in automated characterization of complex atherosclerotic lesions

M. L. Olender; Y. Niu; D. Marlevi; E. R. Edelman; F. R. Nezami 

Computerized Medical Imaging And Graphics. 2022-04-01. Vol. 97, p. 102051. DOI : 10.1016/j.compmedimag.2022.102051.

Exploiting environmental signals to enable policy correlation in large-scale decentralized systems

P. Danassis; Z. D. Erden; B. Faltings 

Autonomous Agents And Multi-Agent Systems. 2022-04-01. Vol. 36, num. 1, p. 13. DOI : 10.1007/s10458-021-09541-7.

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI

F. La Rosa; E. S. Beck; J. Maranzano; R-A. Todea; P. van Gelderen et al. 

Nmr In Biomedicine. 2022-03-31.  p. e4730. DOI : 10.1002/nbm.4730.

Wind-Topo: Downscaling near-surface wind fields to high-resolution topography in highly complex terrain with deep learning

J. Dujardin; M. Lehning 

Quarterly Journal Of The Royal Meteorological Society. 2022-03-29. DOI : 10.1002/qj.4265.

Learnable filter-banks for CNN-based audio applications

H. Peic Tukuljac; B. Ricaud; N. Aspert; L. Colbois 

2022-03-28. 5th Northern Lights Deep Learning Conference (NLDL 2022), Tromsø, Norway, January 10-12, 2022. DOI : 10.7557/18.6279.

A Deep-Learning Approach to Side-Channel Based CPU Disassembly at Design Time

H. Fendri; M. Macchetti; J. Perrine; M. Stojilovic 

2022-03-22. 25th Design, Automation and Test in Europe Conference and Exhibition (DATE), Antwerp, Belgium [Virtual], March 14-23, 2022. p. 670-675. DOI : 10.23919/DATE54114.2022.9774531.

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

R. Ignatans; M. Ziatdinov; R. Vasudevan; M. Valleti; V. Tileli et al. 

Advanced Functional Materials. 2022-03-04.  p. 2100271. DOI : 10.1002/adfm.202100271.

Statistical distortion of supervised learning predictions in optical microscopy induced by image compression

E. Pomarico; C. Schmidt; F. Chays; D. Nguyen; A. Planchette et al. 

Scientific Reports. 2022-03-02. Vol. 12, num. 1, p. 3464. DOI : 10.1038/s41598-022-07445-4.

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

J. Su; Z. Wen; T. Lin; Y. Guan 

Proceedings Of The Acm On Interactive Mobile Wearable And Ubiquitous Technologies-Imwut. 2022-03-01. Vol. 6, num. 1. DOI : 10.1145/3517252.

A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices

V. Uhlmann; L. Donati; D. Sage 

Ieee Signal Processing Magazine. 2022-03-01. Vol. 39, num. 2, p. 73-86. DOI : 10.1109/MSP.2021.3123589.

Semi-supervised Active Salient Object Detection

Y. Lv; B. Liu; J. Zhang; Y. Dai; A. Li et al. 

Pattern Recognition. 2022-03-01. Vol. 123, p. 108364. DOI : 10.1016/j.patcog.2021.108364.

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

S. Sadrizadeh; H. Otroshi-Shahreza; F. Marvasti 

Signal Processing. 2022-03-01. Vol. 192, p. 108378. DOI : 10.1016/j.sigpro.2021.108378.

Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers

D. M. Sima; M. Bach Cuadra; T. B. Dyrby; K. Van Leemput 

Frontiers In Neuroscience. 2022-02-18. Vol. 16, p. 841807. DOI : 10.3389/fnins.2022.841807.

Magnetic control of tokamak plasmas through deep reinforcement learning

J. Degrave; F. Felici; J. Buchli; M. Neunert; B. Tracey et al. 

Nature. 2022-02-16. Vol. 602, num. 7897, p. 414-419. DOI : 10.1038/s41586-021-04301-9.

High-speed identification of suspended carbon nanotubes using Raman spectroscopy and deep learning

J. Zhang; M. L. Perrin; L. Barba; J. Overbeck; S. Jung et al. 

Microsystems & Nanoengineering. 2022-02-10. Vol. 8, num. 1, p. 19. DOI : 10.1038/s41378-022-00350-w.

Automatic table detection and classification in large-scale newspaper archives

A. Vernet 


Photo-astrometric distances, extinctions, and astrophysical parameters for Gaia EDR3 stars brighter than G=18.5

F. Anders; A. Khalatyan; A. B. A. Queiroz; C. Chiappini; J. Ardevol et al. 

Astronomy & Astrophysics. 2022-02-07. Vol. 658, p. A91. DOI : 10.1051/0004-6361/202142369.

Deep Learning Detection of GPS Spoofing

O. Jullian; B. Otero; M. Stojilović; J. J. Costa; J. Verdú et al. 

2022-02-02. 7th International Conference Machine Learning, Optimization, and Data Science (LOD 2021), Grasmere, UK, October 4-8, 2021. p. 527-540. DOI : 10.1007/978-3-030-95467-3_38.

Deep MinCut: Learning Node Embeddings by Detecting Communities

C. T. Duong; T. T. Nguyen; T-D. Hoang; H. Yin; M. Weidlich et al. 

Pattern Recognition. 2022-02-01. Vol. 134, p. 109126. DOI : 10.1016/j.patcog.2022.109126.

Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques

L. Yao; B. Zhu; M. Shoaran 

Journal Of Neural Engineering. 2022-02-01. Vol. 19, num. 1, p. 016037. DOI : 10.1088/1741-2552/ac4ed1.

Align, then memorise: the dynamics of learning with feedback alignment*

M. Refinetti; S. D’Ascoli; R. Ohana; S. Goldt 

Journal Of Physics A-Mathematical And Theoretical. 2022-01-28. Vol. 55, num. 4, p. 044002. DOI : 10.1088/1751-8121/ac411b.