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.


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.

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. 8th International Conference on Learning Representations, Addis Ababa, Ethiopia, April 26-30, 2020.


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. 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.

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. 

Nature 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.

Collaborative Sampling in Generative Adversarial Networks

Y. Liu; P. A. Kothari; A. Alahi 

2019-11-22. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, USA, February 7-12, 2020.

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.

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.

SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion

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

2019-10-27. 2019 International Conference on Computer Vision (ICCV 2019), Seoul, South Korea, 27-10, 2019.

Detecting the Unexpected via Image Resynthesis

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

2019-10-27. ICCV 2019 : IEEE International Conference on Computer Vision, Seoul, South Korea, Oct 27, 2019 – Nov 3, 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 


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.

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.

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.

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.

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.

Topology classification with deep learning to improve real-time event selection at the LHC

T. Q. Nguyen; D. Weitekamp; D. Anderson; R. Castello; O. Cerri et al. 

2019-08-31. DOI : 10.1007/s41781-019-0028-1.

Caries Detection with Near-Infrared Transillumination Using Deep Learning

F. Casalegno; T. Newton; R. Daher; M. Abdelaziz; A. Lodi-Rizzini et al. 

Journal of Dental Research. 2019-08-26.  p. 0022034519871884. DOI : 10.1177/0022034519871884.

Metasurface-Based Molecular Biosensing Aided by Artificial Intelligence

A. Tittl; A. John-Herpin; A. Leitis; E. R. Arvelo; H. Altug 

Angewandte Chemie-International Edition. 2019-08-08. DOI : 10.1002/anie.201901443.

Differentiating Parkinson’s disease motor subtypes using automated volume-based morphometry incorporating white matter and deep gray nuclear lesion load

E. Fang; C. N. Ann; B. Marechal; J. X. Lim; S. Y. Z. Tan et al. 

Journal Of Magnetic Resonance Imaging. 2019-07-31. DOI : 10.1002/jmri.26887.

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images

J. C. Caicedo; J. Roth; A. Goodman; T. Becker; K. W. Karhohs et al. 

Cytometry Part A. 2019-07-16. DOI : 10.1002/cyto.a.23863.

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. 2019-07-14. 

Jamming transition as a paradigm to understand the loss landscape of deep neural networks

M. Geiger; S. Spigler; S. d’Ascoli; L. Sagun; M. Baity-Jesi et al. 

Physical Review E. 2019-07-11. Vol. 100, num. 1, p. 012115. DOI : 10.1103/PhysRevE.100.012115.

A deep learning approach to Cadastral Computing

S. Ares Oliveira; I. di Lenardo; B. Tourenc; F. Kaplan 

2019-07-11. Digital Humanities Conference,, Utrecht, Netherlands, July 8-12, 2019.

Mirror, Mirror, on the Wall, Who’s Got the Clearest Image of Them All?—A Tailored Approach to Single Image Reflection Removal

D. Heydecker; G. Maierhofer; A. I. Aviles-Rivera; F. Qingnan; D. Chen et al. 

IEEE Transactions on Image Processing. 2019-07-01. Vol. 28, num. 12, p. 6185-6197. DOI : 10.1109/TIP.2019.2923559.

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

M. Shardlow; M. Ju; M. Li; C. O’Reilly; E. Iavarone et al. 

Neuroinformatics. 2019-07-01. Vol. 17, num. 3, p. 391-406. DOI : 10.1007/s12021-018-9404-y.

Stochastic Zeroth-Order Optimisation Algorithms with Variance Reduction

A. Ajalloeian / S. U. Stich; M. Jaggi (Dir.)  

EPFL, 2019-06-21. 

Geometric Deep Learning for Volumetric Computational Fluid Dynamics

L. Zampieri 


Spherical Convolutionnal Neural Networks: Empirical Analysis of SCNNs

F. Gusset 


Neural Scene Decomposition for Multi-Person Motion Capture

H. Rhodin; V. Constantin; I. Katircioglu; M. Salzmann; P. Fua 

2019-06-20. Computer Vision and Patter Recognition (CVPR).

Context-Aware Crowd Counting

W. Liu; M. Salzmann; P. Fua 

2019-06-20. Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, June 16-20, 2019.

A comparison of model-parallel training methods for deep learning

P. Kang 


MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

L. Bertoni; S. Kreiss; A. Alahi 

2019-06-07. International Conference on Computer Vision (ICCV), Seoul, Korea, October 27- November 2, 2019 .

Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends

A. Hirschmann; J. Cyriac; B. Stieltjes; T. Kober; J. Richiardi et al. 

Seminars In Musculoskeletal Radiology. 2019-06-01. Vol. 23, num. 3, p. 304-311. DOI : 10.1055/s-0039-1684024.

Design of an Always-On Deep Neural Network-Based 1-mu W Voice Activity Detector Aided With a Customized Software Model for Analog Feature Extraction

M. Yang; C-H. Yeh; Y. Zhou; J. P. Cerqueira; A. A. Lazar et al. 

Ieee Journal Of Solid-State Circuits. 2019-06-01. Vol. 54, num. 6, p. 1764-1777. DOI : 10.1109/JSSC.2019.2894360.

Improving speech embedding using crossmodal transfer learning with audio-visual data

N. Le; J-M. Odobez 

Multimedia Tools and Applications. 2019-06-01. Vol. 78, num. 11, p. 15681-15704. DOI : 10.1007/s11042-018-6992-3.

Learning from droplet flows in microfluidic channels using deep neural networks

P. Hadikhani; N. Borhanil; S. M. H. Hashemi; D. Psaltis 

Scientific Reports. 2019-05-31. Vol. 9, p. 8114. DOI : 10.1038/s41598-019-44556-x.

Deep Drone Racing: From Simulation to Reality with Domain Randomization

A. Loquercio; E. Kaufmann; R. Ranftl; A. Dosovitskiy; V. Koltun et al. 


Enhancing subwavelength image recognition with resonant metamaterial lenses

B. Orazbayev; R. Fleury 

URSI Commission B International Symposium on Electromagnetic Theory (EMTS 2019), San Diego, United Stated, 27-31 May 2019.

Feed-forwards meet recurrent networks in vehicle trajectory prediction

M. Bahari; A. Alahi 

2019-05-15. STRC.

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

B. Bozorgtabar; M. S. Rad; H. K. Ekenel; J-P. Thiran 

2019-05-14. The 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2019), Lille, France, May 14 -18, 2019. p. 230-237.

Audio Feature Extraction with Convolutional Neural Autoencoders with Application to Voice Conversion

G. Elhami; R. M. Weber 

2019-05-12. May 12-17, 2019.

Local SGD Converges Fast and Communicates Little

S. U. Stich 

2019-05-06. ICLR 2019 – International Conference on Learning Representations, New Orleans, USA, May 6-9, 2019.

Incremental Learning Meets Reduced Precision Networks

Y. Hu; T. Delbruck; S-C. Liu 

2019-05-01. 2019 IEEE International Symposium on Circuits and Systems (ISCAS), Sapporo, Japan, May 26-28, 2019. p. 1-5. DOI : 10.1109/ISCAS.2019.8702541.

Low-rank and sparse subspace modeling of speech for DNN based acoustic modeling

P. Dighe; A. Asaei; H. Bourlard 

Speech Communication. 2019-05-01. Vol. 109, p. 34-45. DOI : 10.1016/j.specom.2019.03.004.

MATHICSE Technical Report: Constraint-Aware Neural Networks for Riemann Problems

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


Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

B. Bozorgtabar; D. Mahapatra; H. von Teng; A. Pollinger; L. Ebner et al. 

Computer Vision and Image Understanding (CVIU). 2019-04-17. 

Neural network training for cross-protocol radiomic feature standardization in computed tomography

V. Andrearczyk; A. Depeursinge; H. Muller 

Journal Of Medical Imaging. 2019-04-01. Vol. 6, num. 2, p. 024008. DOI : 10.1117/1.JMI.6.2.024008.

Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks

L. Ge; H. Liang; J. Yuan; D. Thalmann 

Ieee Transactions On Pattern Analysis And Machine Intelligence. 2019-04-01. Vol. 41, num. 4, p. 956-970. DOI : 10.1109/TPAMI.2018.2827052.

DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications

N. Perraudin; M. Defferrard; T. Kacprzak; R. Sgier 

Astronomy And Computing. 2019-04-01. Vol. 27, p. 130-146. DOI : 10.1016/j.ascom.2019.03.004.

Learning Vision-Based Quadrotor Control in User Proximity

D. Mantegazza; J. Guzzi; L. M. Gambardella; A. Giusti 

2019-03-25. 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Daegu, Korea (South), March 11-14, 2019. p. 369-369. DOI : 10.1109/HRI.2019.8673022.

Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing

V. Camus; C. Enz; M. Verhelst 


A computer vision system for deep learning-based detection of patient mobilization activities in the ICU

S. Yeung; F. Rinaldo; J. Jopling; B. Liu; R. Mehra et al. 

Npj Digital Medicine. 2019-03-01. Vol. 2, p. 11. DOI : 10.1038/s41746-019-0087-z.

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

B. Illing; W. Gerstner; J. Brea 


Real-Time Wide-Baseline Place Recognition Using Depth Completion

F. Maffra; L. Teixeira; Z. Chen; M. Chli 

IEEE Robotics and Automation Letters. 2019-01-29. Vol. 4, num. 2, p. 1525-1532. DOI : 10.1109/LRA.2019.2895826.

Challenges and implemented technologies used in autonomous drone racing

H. Moon; J. Martinez-Carranza; T. Cieslewski; M. Faessler; D. Falanga et al. 

Intelligent Service Robotics. 2019-01-24. Vol. 12, num. 2, p. 137-148. DOI : 10.1007/s11370-018-00271-6.

Modular Sensor Fusion for Semantic Segmentation

H. Blum; A. Gawel; R. Siegwart; C. Cadena 

2019-01-07. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018. p. 3670-3677. DOI : 10.1109/IROS.2018.8593786.

PassGAN: A Deep Learning Approach for Password Guessing

B. Hitaj; P. Gasti; G. Ateniese; F. Perez-Cruz 

2019-01-01. 17th International Conference on Applied Cryptography and Network Security (ACNS), Bogota, Colombia, Jun 05-07, 2019. p. 217-237. DOI : 10.1007/978-3-030-21568-2_11.

Architectural Sampling: A Formal Basis for Machine-Learnable Architecture

I. C. B. Koh / J. Huang (Dir.)  

Lausanne, EPFL, 2019. 

Mobile Robotic Painting of Texture

M. El Helou; S. Mandt; A. Krause; P. Beardsley 

2019-01-01. International Conference on Robotics and Automation (ICRA), Montreal, CANADA, May 20-24, 2019. p. 640-647.

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

C. Chen; Y. Liu; S. Kreiss; A. Alahi 

2019-01-01. International Conference on Robotics and Automation (ICRA), Montreal, CANADA, May 20-24, 2019. p. 6015-6022.

Byzantine tolerant gradient descent for distributed machine learning with adversaries

P. Blanchard; E. M. El Mhamdi; R. Guerraoui; J. Stainer 



Trustworthy speaker recognition with minimal prior knowledge using neural networks

H. Muckenhirn / H. Bourlard; M. Magimai Doss (Dir.)  

Lausanne, EPFL, 2019. 

On Problem Formulation, Efficient Modeling and Deep Neural Networks for High-Quality Ultrasound Imaging

D. Perdios; A. Besson; F. Martinez; M. Vonlanthen; M. Arditi et al. 

2019-01-01. 53rd Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, Mar 20-22, 2019.

Language Independent Query by Example Spoken Term Detection

D. Ram / H. Bourlard (Dir.)  

Lausanne, EPFL, 2019. 


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


On the Evaluation and Real-World Usage Scenarios of Deep Vessel Segmentation for Funduscopy

T. Laibacher; A. Anjos 


Detection of Age-Induced Makeup Attacks on Face Recognition Systems Using Multi-Layer Deep Features

K. Kotwal; Z. Mostaani; S. Marcel 


Citizen Visual Search Engine: Detection and Curation of Urban Objects

I. Koh; J. Huang 

2019-01-01. 18th International Conference on Computer-Aided Architectural Design (CAAD Futures) – Hello, Culture, Daejeon, South Korea, June 26-28, 2019. p. 168-182. DOI : 10.1007/978-981-13-8410-3_13.

UAV-Based Situational Awareness System Using Deep Learning

R. Geraldes; A. Goncalves; T. Lai; M. Villerabel; W. Deng et al. 

IEEE Access. 2019-01-01. Vol. 7, p. 122583-122594. DOI : 10.1109/ACCESS.2019.2938249.

Deep learning assisted image transmission in multimode fibers

B. Rahmani; D. Loterie; G. Konstantinou; D. Psaltis; C. Moser 

2019-01-01. Conference on Adaptive Optics and Wavefront Control for Biological Systems V, held at SPIE BiOS, San Francisco, CA, Feb 03-04, 2019. p. 108860N. DOI : 10.1117/12.2508383.

Deep Spline Networks With Control Of Lipschitz Regularity

S. Aziznejad; M. Unser 

2019-01-01. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, ENGLAND, May 12-17, 2019. p. 3242-3246.

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

B. W. Denkinger; F. Ponzina; S. S. Basu; A. Bonetti; S. Balási et al. 

IEEE Design & Test. 2019. DOI : 10.1109/MDAT.2019.2947282.

Remote Sensing meets Deep Learning: Exploiting Spatio-Temporal-Spectral Satellite Images for Early Wildfire Detection

T. C. Phan; T. T. Nguyen 


Abstract Text Summarization: A Low Resource Challenge

S. Parida; P. Motlicek 

2019. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), HongKong, China, p. 5.

Understanding and Visualizing Raw Waveform-based CNNs

H. Muckenhirn; V. Abrol; M. Magimai.-Doss; S. Marcel 

2019. Proceedings of Interspeech.

Tampered Speaker Inconsistency Detection with Phonetically Aware Audio-visual Features

P. Korshunov; M. Halstead; D. Castan; M. Graciarena; M. McLaren et al. 

2019. International Conference on Machine Learning.

Processing Megapixel Images with Deep Attention-Sampling Models

A. Katharopoulos; F. Fleuret 

2019. Proceedings of International Conference on Machine Learning.

Zero-Learning Fast Medical Image Fusion

F. Lahoud; S. Süsstrunk 

2019. 22nd International Conference on Information Fusion (FUSION 2019), Ottawa, Canada, July 2-5, 2019.

Overcoming Multi-model Forgetting

Y. Benyahia; K. Yu; K. B. Smires; M. Jaggi; A. C. Davison et al. 

2019. ICML 2019 – 36th International Conference on Machine Learning, Long Beach, California, USA, June 09-15, 2019. p. 594-603.

Generating Artificial Data for Private Deep Learning

A. Triastcyn; B. Faltings 


Geometry Aware Convolutional Filters for Omnidirectional Images Representation

R. Khasanova; P. Frossard 

2019. ICML 2019 – 36th International Conference on Machine Learning, Long Beach, CA, USA, Jan 18-23, 2019. p. 3351-3359.

A Representer Theorem for Deep Neural Networks

M. Unser 

Journal Of Machine Learning Research. 2019-01-01. Vol. 20.

Graph Laplacians for Rotation Equivariant Convolutional Neural Networks

M. Milani 


Graph-based image representation learning

R. Khasanova / P. Frossard (Dir.)  

Lausanne, EPFL, 2019. 

Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

M. El Helou; S. Süsstrunk 


Deep Learning for Music: Similarity Search and Beyond

M. G. M. A. Devaux 


Deep Micro-Dictionary Learning and Coding Network

H. Tang; H. Wei; W. Xiao; W. Wang; D. Xu et al. 

2019-01-01. 19th IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Village, HI, Jan 07-11, 2019. p. 386-395. DOI : 10.1109/WACV.2019.00047.

Rethinking Person Re-Identification with Confidence

G. Adaimi; S. Kreiss; A. Alahi 

2019. arXiv.