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.

2022

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.

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.

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.

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.

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-+. 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-+. DOI : 10.1126/science.abn2100.

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 

2022-07-08.

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.

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.

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. 

arXiv. 2022-04-07. 

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.

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 

2022-02-08.

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.

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.

Is Your Time Well Spent Online?: Focusing on Quality Experiences Through a User-Centered Recommendation Algorithm and Simulation Model

R. Islambouli; S. Ingram; D. Gillet 

2022-01-25. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), [Virtual event] Pasadena, CA, USA , December 13-16, 2021. DOI : 10.1109/ICMLA52953.2021.00171.

New particle formation event detection with Mask R-CNN

P. Su; J. Joutsensaari; L. Dada; M. A. Zaidan; T. Nieminen et al. 

Atmospheric Chemistry and Physics. 2022-01-25. Vol. 22, num. 2, p. 1293-1309. DOI : 10.5194/acp-22-1293-2022.

Learning to image and compute with multimode optical fibers

B. Rahmani; I. Oguz; U. Tegin; J-l. Hsieh; D. Psaltis et al. 

Nanophotonics. 2022-01-21. Vol. 11, num. 6, p. 1071–1082. DOI : 10.1515/nanoph-2021-0601.

Euclid preparation XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models

H. Bretonniere; M. Huertas-Company; A. Boucaud; F. Lanusse; E. Jullo et al. 

Astronomy & Astrophysics. 2022-01-18. Vol. 657, p. A90. DOI : 10.1051/0004-6361/202141393.

Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current Approaches, Open Challenges, and Future Opportunities

C. Persello; J. D. Wegner; R. Haensch; D. Tuia; P. Ghamisi et al. 

Ieee Geoscience And Remote Sensing Magazine. 2022-01-13. DOI : 10.1109/MGRS.2021.3136100.

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

M. El Helou; S. Süsstrunk 

IEEE Transactions on Image Processing. 2022-01-08. Vol. 31, p. 1-13. DOI : 10.1109/TIP.2022.3143006.

In-Memory Hardware and Architectural Extensions for Workloads Acceleration

W. A. Simon / D. Atienza Alonso (Dir.)  

Lausanne, EPFL, 2022. 

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

V. Vikashini; H. Salam; J. Nasir; B. Bruno; O. Celiktutan 

2022. 24th ACM International Conference on Multimodal Interaction (ICMI), Bangalore, India, November 7-11, 2022.

Deep Reinforcement Learning for Random Access in Machine-Type Communication

M. Awais Jadoon; A. Pastore; M. Navarro; F. Perez-Cruz 

2022-01-01. IEEE Wireless Communications and Networking Conference (IEEE WCNC), Austin, TX, Apr 10-13, 2022. p. 2553-2558. DOI : 10.1109/WCNC51071.2022.9771953.

Theory of Deep Learning: Neural Tangent Kernel and Beyond

A. U. Jacot-Guillarmod / C. Hongler (Dir.)  

Lausanne, EPFL, 2022. 

Robustness and invariance properties of image classifiers

A. Modas / P. Frossard (Dir.)  

Lausanne, EPFL, 2022. 

Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks.

C. Liu / S. Süsstrunk; M. Salzmann (Dir.)  

Lausanne, EPFL, 2022. 

Understanding Deep Neural Networks using Adversarial Attacks

K. K. Nakka / P. Fua; M. Salzmann (Dir.)  

Lausanne, EPFL, 2022. 

Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation

S. Anagnostopoulos; M. Piggott 

2022-01-01. WindEurope Electric City Conference, Copenhagen, DENMARK, Nov 22-26, 2021. p. 012011. DOI : 10.1088/1742-6596/2151/1/012011.

Deploying an Instance Segmentation Algorithm to Implement Social Distancing for Prosthetic Vision

D. De Luca; S. Moccia; S. Micera 

2022-01-01. IEEE International Conference on Pervasive Computing and Communications (PerCom), ELECTR NETWORK, Mar 21-25, 2022. DOI : 10.1109/PerComWorkshops53856.2022.9767213.

A hardware/software co-design vision for deep learning at the edge

F. Ponzina; S. Machetti; M. A. Rios; B. W. Denkinger; A. S. J. Levisse et al. 

IEEE Micro – Special Issue on Artificial Intelligence at the Edge. 2022. DOI : 10.1109/MM.2022.3195617.

On SGD with Momentum

M. Plattner 

2022.

Advanced Techniques in Optical Diffraction Tomography

A. B. Sayed Ayoub Mohamed Emam / D. Psaltis (Dir.)  

Lausanne, EPFL, 2022. 

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

D. Tomar; B. Bozorgtabar; M. Lortkipanidze; G. Vray; M. S. Rad et al. 

2022-01-01. 22nd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, Jan 04-08, 2022. p. 1737-1747. DOI : 10.1109/WACV51458.2022.00180.

Algorithms for Efficient and Robust Distributed Deep Learning

T. Lin / M. Jaggi; B. Falsafi (Dir.)  

Lausanne, EPFL, 2022. 

Where does the engram come from? Study of prefrontal cortex inputs during memory consolidation

L. P. Dixsaut / J. Gräff (Dir.)  

Lausanne, EPFL, 2022. 

Simple Yet Effective Action Recognition for Autonomous Driving

W. Xiong; L. Bertoni; T. Mordan; A. Alahi 

2022. 11th Triennial Symposium on Transportation Analysis Conference (TRISTAN XI), Mauritius Island, June 19-25, 2022.

Structure-preserving approaches and data-driven closure modeling for model order reduction

N. Ripamonti / J. S. Hesthaven (Dir.)  

Lausanne, EPFL, 2022. 

Object Priors for Volumetric Image Segmentation

P. U. Wickramasinghe / P. Fua (Dir.)  

Lausanne, EPFL, 2022. 

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

E. Boursier; L. Pillaud-Vivien; N. Flammarion 

2022

Learning rich optical embeddings for privacy-preserving lensless image classification

E. Bezzam; M. Vetterli; M. Simeoni 

2022

Automatic pathological speech assessment

P. Janbakhshi / H. Bourlard; I. Kodrasi (Dir.)  

Lausanne, EPFL, 2022. 

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

A. Katharopoulos / F. Fleuret; P. Frossard (Dir.)  

Lausanne, EPFL, 2022. 

Learning to sample in Cartesian MRI

T. Sanchez / V. Cevher (Dir.)  

Lausanne, EPFL, 2022. 

Optimization Over Banach Spaces: A Unified View on Supervised Learning and Inverse Problems

S. Aziznejad / M. Unser (Dir.)  

Lausanne, EPFL, 2022. 

Graph Representation Learning with Optimal Transport: Analysis and Applications

E. Simou / P. Frossard (Dir.)  

Lausanne, EPFL, 2022. 

Using Animal Motion Capture to Learn Neural Representations

S. Günel / P. Fua; P. P. Ramdya (Dir.)  

Lausanne, EPFL, 2022. 

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

T. Yu / J-P. Thiran; M. Bach Cuadra (Dir.)  

Lausanne, EPFL, 2022. 

Deep learning accelerated prediction of the permeability of fibrous microstructures

B. Caglar; G. Broggi; M. A. Ali; L. Orgéas; V. Michaud 

Composites Part A: Applied Science and Manufacturing. 2022. Vol. 158, p. 106973. DOI : 10.1016/j.compositesa.2022.106973.

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

E. Remelli / P. Fua (Dir.)  

Lausanne, EPFL, 2022. 

Sparsest Univariate Learning Models Under Lipschitz Constraint

S. Aziznejad; T. Debarre; M. Unser 

Ieee Open Journal Of Signal Processing. 2022-01-01. Vol. 3, p. 140-154. DOI : 10.1109/OJSP.2022.3157082.

Towards automating de novo protein design for novel functionalities: controlling protein folds and protein-protein interactions

Z. Harteveld / B. E. Ferreira De Sousa Correia (Dir.)  

Lausanne, EPFL, 2022. 

Targeting molecular surfaces to engineer novel protein-based immunogens and inhibitors

S. Wehrle / B. E. Ferreira De Sousa Correia (Dir.)  

Lausanne, EPFL, 2022. 

Essays in Empirical Asset Pricing

A. A. Marchal / P. Collin Dufresne; J. Hugonnier (Dir.)  

Lausanne, EPFL, 2022. 

Reshaping Perception for Autonomous Driving with Semantic Keypoints

L. Bertoni / A. M. Alahi (Dir.)  

Lausanne, EPFL, 2022. 

Learning of physical systems: from inference to control

B. Rahmani / C. Moser (Dir.)  

Lausanne, EPFL, 2022. 

Learning to Align Sequential Actions in the Wild

W. Liu; B. Tekin; H. Coskun; V. Vineet; P. Fua et al. 

2022. CVPR 2022 : IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans , United States, June 21 – 24, 2022.

TEE-based decentralized recommender systems: The raw data sharing redemption

A. Dhasade; N. Dresevic; A-M. Kermarrec; R. Pires 

2022. 36th IEEE International Parallel & Distributed Processing Symposium (IPDPS ’22), Virtual, May 30 – June 3 2022. DOI : 10.1109/IPDPS53621.2022.00050.

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

F. La Rosa / J-P. Thiran; M. Bach Cuadra (Dir.)  

Lausanne, EPFL, 2022.