Recherche

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.

2020

Overview of CLEF HIPE 2020: Named Entity Recognition and Linking on Historical Newspapers

M. Ehrmann; M. Romanello; A. Flückiger; S. Clematide 

2020-09-15. 11th International Conference of the CLEF Association – CLEF 2020, Thessaloniki, Greece, September 22–25, 2020. p. 288–310. DOI : 10.1007/978-3-030-58219-7_21.

Precise Hand Finger Width Estimation via RGB-D Data

M. Nobar 

2020-08-31.

Musical Source Separation

A. Mocanu 

2020-08-14.

Far-Field Subwavelength Acoustic Imaging by Deep Learning

B. Orazbayev; R. Fleury 

Physical Review X. 2020-08-07. Vol. 10, p. 031029. DOI : 10.1103/PhysRevX.10.031029.

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

B. Zhu; M. Farivar; M. Shoaran 

IEEE Transactions on Biomedical Circuits and Systems. 2020-08-01. Vol. 14, num. 4, p. 692-704. DOI : 10.1109/TBCAS.2020.3004544.

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

S. Tortora; S. Ghidoni; C. Chisari; S. Micera; F. Artoni 

Journal Of Neural Engineering. 2020-08-01. Vol. 17, num. 4, p. 046011. DOI : 10.1088/1741-2552/ab9842.

Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

E. Taghizadeh; O. Truffer; F. Becce; S. Eminian; S. Gidoin et al. 

European Radiology. 2020-07-22. DOI : 10.1007/s00330-020-07070-7.

Benefiting from Multitask Learning to Improve Single Image Super-Resolution

M. S. Rad; B. Bozorgtabar; C. Musat; U-V. Marti; M. Basler et al. 

Neurocomputing. 2020-07-20. Vol. 398, num. 398, p. 304-313.

Redundant features can hurt robustness to distributions shift

G. Ortiz Jimenez; A. Modas; S. M. Moosavi Dezfooli; P. Frossard 

Uncertainty & Robustness in Deep Learning Workshop (ICML 2020).

GarNet++: Improving Fast and Accurate Static 3D Cloth Draping by Curvature Loss

E. Gündogdu; V. Constantin; S. Parashar; A. Seifoddini; M. Dang et al. 

IEEE Transactions On Pattern Analysis And Machine Intelligence (PAMI). 2020-07-14. 

Human Trajectory Forecasting in Crowds: A Deep Learning Perspective

P. Kothari; S. Kreiss; A. Alahi 

2020-07-07

Understanding and Improving Fast Adversarial Training

M. Andriushchenko; N. Flammarion 

2020-07-06

Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments

D. Morone; A. Marazza; T. J. Bergmann; M. Molinari 

Molecular Biology Of The Cell. 2020-07-01. Vol. 31, num. 14, p. 1512-1524. DOI : 10.1091/mbc.E20-04-0269.

Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

F. La Rosa; A. Abdulkadir; M. J. Fartaria; R. Rahmanzadeh; P-J. Lu et al. 

NeuroImage: Clinical. 2020-06-30. Vol. 27, p. 102335. DOI : 10.1016/j.nicl.2020.102335.

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

F. Croce; M. Andriushchenko; N. Singh; N. Flammarion; M. Hein 

2020-06-23

Detecting solar rooftop photovoltaic panels in aerial images using neural networks: a transfer learning approach

S. Roquette 

2020-06-19.

On the Experimental Transferability of Spectral Graph Convolutional Networks

A. Nilsson 

2020-06-19.

Geometric deep learning for medium-range weather prediction

I. Llorens Jover 

2020-06-19.

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

M. Villamizar; A. Martinez-Gonzalez; O. Canevet; J. -M. Odobez 

Machine Vision And Applications. 2020-06-17. Vol. 31, num. 6, p. 41. DOI : 10.1007/s00138-020-01089-y.

Shape Reconstruction by Learning Differentiable Surface Representations

J. Bednarík; S. Parashar; E. Gündogdu; M. Salzmann; P. Fua 

2020-06-14. 2020 CVPR – Computer Vision and Pattern Recognition, Seattle, USA, June 14-16, 2020.

Editorial: Computational Pathology

B. Bozorgtabar; D. Mahapatra; I. Zlobec; T. T. Rau; J-P. Thiran 

Frontiers In Medicine. 2020-06-09. Vol. 7, p. 245. DOI : 10.3389/fmed.2020.00245.

Joint Segmentation and Path Classification of Curvilinear Structures

A. Mosinska; M. Kozinski; P. Fua 

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). 2020-06-01. Vol. 42, num. 6, p. 1515-1521. DOI : 10.1109/TPAMI.2019.2921327.

Joint Human Pose Estimation and Stereo 3D Localization

W. Deng; L. Bertoni; S. Kreiss; A. Alahi 

2020-06-01. International Conference on Robotics and Automation (ICRA), paris, france, May 31th, June 4th 2020.

Deep Learning-Based Image Classification through a Multimode Fiber in the Presence of Wavelength Drift

E. Kakkava; N. Borhani; B. Rahmani; U. Teğin; C. Moser et al. 

Applied Sciences. 2020-05-30. Vol. 10, num. 11, p. 3816. DOI : 10.3390/app10113816.

Accurate deep neural network inference using computational phase-change memory

V. Joshi; M. Le Gallo; S. Haefeli; I. Boybat; S. R. Nandakumar et al. 

Nature Communications. 2020-05-18. Vol. 11, num. 1. DOI : 10.1038/s41467-020-16108-9.

Noise-Resilient and Interpretable Epileptic Seizure Detection

A. Hitchcock Thomas; A. Aminifar; D. Atienza Alonso 

2020-05-17. IEEE International Symposium on Circuits and Systems – ISCAS 2020, Seville, Spain, May 17-21, 2020.

Constraint-aware neural networks for Riemann problems

J. Magiera; D. Ray; J. S. Hesthaven; C. Rohde 

Journal Of Computational Physics. 2020-05-15. Vol. 409, p. 109345. DOI : 10.1016/j.jcp.2020.109345.

Multi-View Shape Estimation of Transparent Containers

A. Xompero; R. Sanchez-Matilla; A. Modas; P. Frossard; A. Cavallaro 

2020-05-08. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), [Online event], May 4-8, 2020. DOI : 10.1109/ICASSP40776.2020.9054112.

Optimization for Reinforcement Learning: From a single agent to cooperative agents

D. Lee; N. He; P. Kamalaruban; V. Cevher 

Ieee Signal Processing Magazine. 2020-05-01. Vol. 37, num. 3, p. 123-135. DOI : 10.1109/MSP.2020.2976000.

Unsupervised Stereo Matching Using Confidential Correspondence Consistency

S. Joung; S. Kim; K. Park; K. Sohn 

Ieee Transactions On Intelligent Transportation Systems. 2020-05-01. Vol. 21, num. 5, p. 2190-2203. DOI : 10.1109/TITS.2019.2917538.

Introducing the CLEF 2020 HIPE Shared Task: Named Entity Recognition and Linking on Historical Newspapers

M. Ehrmann; M. Romanello; S. Bircher; S. Clematide 

2020-04-08. ECIR 2020 : 42nd European Conference on Information Retrieval, Lisbon, Portugal, April 14-17, 2020. p. 524-532. DOI : 10.1007/978-3-030-45442-5_68.

ExprADA: Adversarial domain adaptation for facial expression analysis

S. Bozorgtabar; D. Mahapatra; J-P. Thiran 

Pattern Recognition. 2020-04-01. Vol. 100, p. 107111. DOI : 10.1016/j.patcog.2019.107111.

Automated Essay Scoring in Foreign Language Students Based on Deep Contextualised Word Representations

B. Ranković; S. Smirnow; M. Jaggi; M. J. Tomasik 

2020-03-23. LAK20 – 10th International Conference on Learning Analytics & Knowledge, Mars 23, 2020.

Blind Universal Bayesian Image Denoising With Gaussian Noise Level Learning

M. El Helou; S. Süsstrunk 

2020-03-04. IEEE Transactions on Image Processing (TIP). p. 4885 – 4897. DOI : 10.1109/TIP.2020.2976814.

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

P. Maggi; M. J. Fartaria; J. Jorge; F. La Rosa; M. Absinta et al. 

Nmr In Biomedicine. 2020-03-03.  p. e4283. DOI : 10.1002/nbm.4283.

Classification of tokamak plasma confinement states with convolutional recurrent neural networks

F. Matos; V. Menkovski; F. Felici; A. Pau; F. Jenko 

Nuclear Fusion. 2020-03-01. Vol. 60, num. 3, p. 036022. DOI : 10.1088/1741-4326/ab6c7a.

Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

U. Tegin; B. Rahmani; E. Kakkava; N. Borhani; C. Moser et al. 

Apl Photonics. 2020-03-01. Vol. 5, num. 3, p. 030804. DOI : 10.1063/1.5138131.

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy

S. Ali; F. Zhou; B. Braden; A. Bailey; S. Yang et al. 

Scientific Reports. 2020-02-17. Vol. 10, num. 1, p. 2748. DOI : 10.1038/s41598-020-59413-5.

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics

K. Parameswaran; Y-T. Huang; Y-P. Hsieh; P. T. Y. Rolland; C. Shi et al. 

2020-02-14

Collaborative Sampling in Generative Adversarial Networks

Y. Liu; P. A. Kothari; A. Alahi 

2020-02-11. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, USA, February 7-12, 2020. p. 4948-4956. DOI : 10.1609/aaai.v34i04.5933.

Annealing and Replica-Symmetry in Deep Boltzmann Machines

D. Alberici; A. Barra; P. Contucci; E. Mingione 

Journal Of Statistical Physics. 2020-02-05. DOI : 10.1007/s10955-020-02495-2.

Deep-learning projector for optical diffraction tomography

F. Yang; T-A. Pham; H. Gupta; M. Unser; J. Ma 

Optics Express. 2020-02-03. Vol. 28, num. 3, p. 3905-3921. DOI : 10.1364/OE.381413.

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

C. Capelo 

2020-02-03.

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

M. Kozinski; A. Mosinska; M. Salzmann; P. Fua 

Medical Image Analysis. 2020-02-01. Vol. 60, p. 101590. DOI : 10.1016/j.media.2019.101590.

Scaling description of generalization with number of parameters in deep learning

M. Geiger; A. Jacot; S. Spigler; F. Gabriel; L. Sagun et al. 

Journal Of Statistical Mechanics-Theory And Experiment. 2020-02-01. Vol. 2020, num. 2, p. 023401. DOI : 10.1088/1742-5468/ab633c.

Vision based pixel-level bridge structural damage detection using a link ASPP network

W. Deng; Y. Mou; T. Kashiwa; S. Escalera; K. Nagai et al. 

Automation In Construction. 2020-02-01. Vol. 110, p. 102973. DOI : 10.1016/j.autcon.2019.102973.

Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

C. E. R. Schäfer / J-P. R. Kneib (Dir.)  

Lausanne, EPFL, 2020. 

Comparison of crack segmentation using digital image correlation measurements and deep learning

A. Rezaie; R. Achanta; M. Godio; K. Beyer 

Construction and Building Materials. 2020. Vol. 261, p. 1-12, 120474. DOI : 10.1016/j.conbuildmat.2020.120474.

Reconstruction Methods for Cryo-Electron Microscopy: From Model-based to Data-driven

L. Donati / M. Unser; D. Sage (Dir.)  

Lausanne, EPFL, 2020. 

Data Structures and Algorithms for Logic Synthesis in Advanced Technologies

E. Testa / G. De Micheli; M. Soeken (Dir.)  

Lausanne, EPFL, 2020. 

Towards neural network approaches for point cloud compression

E. Alexiou; K. Tung; T. Ebrahimi 

2020. SPIE Optical Engineering + Applications, Online, August 24-28, 2020. p. 1151008. DOI : 10.1117/12.2569115.

W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping

R. Zhou; M. El Helou; D. Sage; T. Laroche; A. Seitz et al. 

2020. European Conference on Computer Vision Workshops 2020, Glasgow, United Kingdom, August 23-28, 2020.

Single Image Deraining Using Time-Lapse Data

J. Cho; S. Kim; D. Min; K. Sohn 

Ieee Transactions On Image Processing. 2020-01-01. Vol. 29, p. 7274-7289. DOI : 10.1109/TIP.2020.3000612.

Towards Real-World Super-Resolution using Deep Neural Networks

R. Zhou / S. Süsstrunk (Dir.)  

Lausanne, EPFL, 2020. 

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

P. T. Sivaprasad; F. Mai; T. Vogels; M. Jaggi; F. Fleuret 

2020. 37th International Conference on Machine Learning, Vienna, Austria.

Redundant features can hurt robustness to distribution shift

G. Ortiz Jimenez; A. Modas; S. M. Moosavi Dezfooli; P. Frossard 

2020. ICML 2020 Workshop on Uncertainty & Robustness in Deep Learning, [Online event], July 17, 2020.

Deep Generative Models and Applications

T. Chavdarova / F. Fleuret (Dir.)  

Lausanne, EPFL, 2020. 

Neural Network Based End-to-End Query by Example Spoken Term Detection

D. Ram; L. Miculicich; H. Bourlard 

Ieee-Acm Transactions On Audio Speech And Language Processing. 2020-01-01. Vol. 28, p. 1416-1427. DOI : 10.1109/TASLP.2020.2988788.

Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data

P. U. Wickramasinghe; E. Remelli; G. Knott; P. Fua 

2020. 23rd International Conference On Medical Image Computing & Computer Assisted Intervention, Lima, Peru, 4-8 OCTOBER 2020.

Dynamic Model Pruning with Feedback

T. Lin; S. U. Stich; L. F. Barba Flores; D. Dmitriev; M. Jaggi 

2020. 8th International Conference on Learning Representations (ICLR), Virtual Conference, Formerly Addis Ababa, Ethiopia, April 26-30, 2020.

Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques

R. Sahu; S. R. Dash; L. A. Cacha; R. R. Poznanski; S. Parida 

Journal of Integrative Neuroscience. 2020. Vol. 19, num. 1, p. 1-9. DOI : 10.31083/j.jin.2020.01.24.

Trustworthy Face Recognition: Improving Generalization of Deep Face Presentation Attack Detection

A. Mohammadi / H. Bourlard; S. Marcel (Dir.)  

Lausanne, EPFL, 2020. 

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

A. Mohammadi; S. Bhattacharjee; S. Marcel 

2020. 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain,

Learning stereo reconstruction with deep neural networks

S. Tulyakov / F. Fleuret; A. Ivanov (Dir.)  

Lausanne, EPFL, 2020. 

Crowding and the Architecture of the Visual System

A. C. Doerig / M. Herzog (Dir.)  

Lausanne, EPFL, 2020. 

Exploration Methodology for BTI-Induced Failures on RRAM-Based Edge AI Systems

A. S. J. Levisse; M. A. Rios; M. Peon Quiros; D. Atienza Alonso 

2020. 45th International Conference on Acoustics, Speech, and Signal Processing _ ICASSP 2020, Barcelona, Spain, 4-6 May, 2020.

Byzantine machine learning

E. M. El Mhamdi; R. Guerraoui; S. Rouault; M. Taziki 

WO2020011361.

2020.

What graph neural networks cannot learn: depth vs width

A. Loukas 

2020. International Conference on Learning Representations, Addis Ababa, Ethiopia, April 26-30, 2020.

Sparse and Parametric Modeling with Applications to Acoustics and Audio

H. Peic Tukuljac / P. Vandergheynst; H. Lissek (Dir.)  

Lausanne, EPFL, 2020. 

Multi-memristive synaptic architectures for training neural networks

I. Boybat Kara / Y. Leblebici; A. Sebastian (Dir.)  

Lausanne, EPFL, 2020. 

Evaluating the search phase of neural architecture search

K. Yu; C. Suito; M. Jaggi; C-C. Musat; M. Salzmann 

2020. ICRL 2020 Eighth International Conference on Learning Representations, Millennium Hall, Addis Ababa, ETHIOPIA, April 26-30, 2020.

Domain-Adaptive Multibranch Networks

R. Bermúdez Chacón; M. Salzmann; P. Fua 

2020. International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 26-30, 2020.

AM-FM DECOMPOSITION OF SPEECH SIGNAL: APPLICATIONS FOR SPEECH PRIVACY AND DIAGNOSIS

P. Motlicek; H. Hermansky; S. Madikeri; A. Prasad; S. Ganapathy 

2020

Enhancing discrete choice models with representation learning

B. Sifringer; V. Lurkin; A. Alahi 

Transportation Research Part B: Methodological. 2020. Vol. 140, p. 236-261. DOI : 10.1016/j.trb.2020.08.006.

2019

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

P. Gainza; F. Sverrisson; F. Monti; E. Rodolà; D. Boscaini et al. 

Nature Methods. 2019-12-09. Vol. 17, pages184–192(2020), p. 184-192. DOI : 10.1038/s41592-019-0666-6.

Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks

M. Unser; M. T. McCann 

Foundations and Trends® in Signal Processing. 2019-12-03. Vol. 13, num. 3, p. 280-359. DOI : 10.1561/2000000101.

Comparing dynamics: deep neural networks versus glassy systems

M. Baity-Jesi; L. Sagun; M. Geiger; S. Spigler; G. Ben Arpus et al. 

Journal Of Statistical Mechanics-Theory And Experiment. 2019-12-01. Vol. 2019, num. 12, p. 124013. DOI : 10.1088/1742-5468/ab3281.

Entropy and mutual information in models of deep neural networks

M. Gabrie; A. Manoel; C. Luneau; J. Barbier; N. Macris et al. 

Journal Of Statistical Mechanics-Theory And Experiment. 2019-12-01. Vol. 2019, num. 12, p. 124014. DOI : 10.1088/1742-5468/ab3430.

Latest advances in aging research and drug discovery

D. Bakula; A. Ablasser; A. Aguzzi; A. Antebi; N. Barzilai et al. 

Aging-Us. 2019-11-30. Vol. 11, num. 22, p. 9971-9981. DOI : 10.18632/aging.102487.

Le fabuleux chantier: Rendre l’intelligence artificielle robustement bénéfique

L. N. Hoang; E. M. El Mhamdi 

EDP Sciences, 2019-11-28.

Single-Sensor Source Localization Using Electromagnetic Time Reversal and Deep Transfer Learning: Application to Lightning

A. Mostajabi; H. Karami; M. Azadifar; A. Ghasemi; M. Rubinstein et al. 

Scientific Reports. 2019-11-22. Vol. 9, num. 1. DOI : 10.1038/s41598-019-53934-4.

A jamming transition from under- to over-parametrization affects generalization in deep learning

S. Spigler; M. Geiger; S. d’Ascoli; L. Sagun; G. Biroli et al. 

Journal Of Physics A-Mathematical And Theoretical. 2019-11-22. Vol. 52, num. 47, p. 474001. DOI : 10.1088/1751-8121/ab4c8b.

Deep learning in the built environment: automatic detection of rooftop solar panels using Convolutional Neural Networks

R. Castello; S. Roquette; M. Esguerra; A. Guerra; J-L. Scartezzini 

2019-11-20. CISBAT 2019 | Climate Resilient Cities – Energy Efficiency & Renewables in the Digital Era, Lausanne, Switzerland, 4–6 September 2019. DOI : 10.1088/1742-6596/1343/1/012034.

Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation

W. Liu; K. M. Lis; M. Salzmann; P. Fua 

2019-11-08. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 4-8, 2019. p. 244-249.

Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task

A. Mohammadshahi; R. P. Lebret; K. Aberer 

2019-11-03. 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Hong Kong, China, November 3-7, 2019. p. 27-33. DOI : 10.18653/v1/D19-6605.

Imaging through multimode fibers using deep learning: The effects of intensity versus holographic recording of the speckle pattern

E. Kakkava; B. Rahmani; N. Borhani; U. Tegin; D. Loterie et al. 

Optical Fiber Technology. 2019-11-01. Vol. 52, p. 101985. DOI : 10.1016/j.yofte.2019.101985.

Learning to Find Unpaired Cross-Spectral Correspondences

S. Jeong; S. Kim; K. Park; K. Sohn 

Ieee Transactions On Image Processing. 2019-11-01. Vol. 28, num. 11, p. 5394-5406. DOI : 10.1109/TIP.2019.2917864.

Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing

V. Camus; L. Mei; C. Enz; M. Verhelst 

IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS). 2019-10-30. Vol. 9, num. 4, p. 697-711. DOI : 10.1109/JETCAS.2019.2950386.

Detecting the Unexpected via Image Resynthesis

K. M. Lis; K. K. Nakka; P. Fua; M. Salzmann 

2019-10-27. IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, SOUTH KOREA, Oct 27-Nov 02, 2019. p. 2152-2161. DOI : 10.1109/ICCV.2019.00224.

What attracts our visual attention? A study on saliency mapping for architectural daylit scenes based on virtual reality data

C. Karmann 

VELUX Daylight Symposium, Paris, France, Octobre 9, 2019.

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

M. Rios; W. A. Simon; A. S. J. Levisse; M. Zapater Sancho; D. Atienza Alonso 

2019-10-09. 

Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images

R. Bermúdez Chacón; O. Altingövde; C. J. Becker; M. Salzmann; P. Fua 

IEEE Transactions on Medical Imaging. 2019-10-04. DOI : 10.1109/TMI.2019.2946462.

DeepFly3D, a deep learning-based approach for 3D limb and appendage tracking in tethered, adult Drosophila

S. Günel; H. Rhodin; D. Morales; J. H. Campagnolo; P. Ramdya et al. 

eLife. 2019-10-04. Vol. 8. DOI : 10.7554/eLife.48571.

2D MoS2 nanopores: ionic current blockade height for clustering DNA events

A. D. Carral; C. S. Sarap; K. Liu; A. Radenovic; M. Fyta 

2D Materials. 2019-10-01. Vol. 6, num. 4, p. 045011. DOI : 10.1088/2053-1583/ab2c38.

Biologically plausible deep learning – but how far can we go with shallow networks?

B. Illing; W. Gerstner; J. Brea 

Neural Networks. 2019-10-01. Vol. 118, p. 90-101. DOI : 10.1016/j.neunet.2019.06.001.

Sim-to-real transfer reinforcement learning for control of thermal effects of an atmospheric pressure plasma jet

M. Witman; D. Gidon; D. B. Graves; B. Smit; A. Mesbah 

Plasma Sources Science and Technology. 2019-09-24. Vol. 28, num. 9, p. 095019. DOI : 10.1088/1361-6595/ab3c15.

Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P-J. Lu et al. 

2019-09-10. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Stockholm, Sweden, September 11-13, 2019. p. 131-356. DOI : 10.1177/1352458519868078.

Learning online combinatorial stochastic policies with deep reinforcement

T. Stocco; A. Alahi 

2019-09-04. European Association for Research in Transportation (hEART), Budapest, September 4-6, 2019.

Deep learning analysis applied to multi-parametric advanced MRI shows higher myelin content and neurite density in juxtacortical lesions compared to periventricular lesions

P. -J. Lu; R. Rahmanzadeh; R. Galbusera; B. Odry; M. Weigel et al. 

2019-09-01. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Stockholm, SWEDEN, Sep 11-13, 2019. p. 241-242.

Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P. -J. Lu et al. 

2019-09-01. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Stockholm, SWEDEN, Sep 11-13, 2019. p. 206-207.