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- Philippe Leray 0001
Ecole Polytechnique de l'université de Nantes, France - Philippe Leray 0002
imec, Leuven, Belgium
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Publication search results
found 102 matches
- 2024
- Jaime Ramírez Castillo, M. Julia Flores, Philippe Leray:
Predicting spotify audio features from Last.fm tags. Multim. Tools Appl. 83(16): 48311-48330 (2024) - Ying-Lin Chen, Jacob Deforce, Vic De Ridder, Bappaditya Dey, Víctor Blanco, Sandip Halder, Philippe Leray:
Towards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS. CoRR abs/2404.05862 (2024) - 2023
- Walid Fathallah, Nahla Ben Amor, Philippe Leray:
An Optimized Quantum Circuit Representation of Bayesian Networks. ECSQARU 2023: 160-171 - Sara Sacchi, Bappaditya Dey, Iacopo Mochi, Sandip Halder, Philippe Leray:
Deep learning denoiser assisted roughness measurements extraction from thin resists with low Signal-to-Noise Ratio(SNR) SEM images: analysis with SMILE. CoRR abs/2310.14815 (2023) - Bappaditya Dey, Anh Tuan Ngo, Sara Sacchi, Víctor Blanco, Philippe Leray, Sandip Halder:
Applying Machine Learning Models on Metrology Data for Predicting Device Electrical Performance. CoRR abs/2312.09462 (2023) - 2022
- Mahmoud Ferhat, Philippe Leray, Mathieu Ritou, Nicolas Le Du:
Iterative knowledge discovery for fault detection in manufacturing systems. KES 2022: 744-753 - Bappaditya Dey, Dipam Goswami, Sandip Halder, Kasem Khalil, Philippe Leray, Magdy A. Bayoumi:
Deep Learning-Based Defect Classification and Detection in SEM Images. CoRR abs/2206.13505 (2022) - Bappaditya Dey, Enrique Dehaerne, Kasem Khalil, Sandip Halder, Philippe Leray, Magdy A. Bayoumi:
Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach. CoRR abs/2211.02185 (2022) - 2021
- Sarah Benikhlef, Philippe Leray, Guillaume Raschia, Montassar Ben Messaoud, Fayrouz Sakly:
Multi-task Transfer Learning for Bayesian Network Structures. ECSQARU 2021: 217-228 - Mathilde Monvoisin, Philippe Leray, Mathieu Ritou:
Unsupervised Co-training of Bayesian Networks for Condition Prediction. IEA/AIE (2) 2021: 577-588 - 2020
- Vahé Asvatourian, Philippe Leray, Stefan Michiels, Emilie Lanoy:
Integrating expert's knowledge constraint of time dependent exposures in structure learning for Bayesian networks. Artif. Intell. Medicine 107: 101874 (2020) - Evan Dufraisse, Philippe Leray, Raphaël Nedellec, Tarek Benkhelif:
Interactive Anomaly Detection in Mixed Tabular Data using Bayesian Networks. PGM 2020: 185-196 - 2019
- Mathilde Monvoisin, Philippe Leray:
Multi-task Transfer Learning for Timescale Graphical Event Models. ECSQARU 2019: 313-323 - Dimitri Antakly, Benoît Delahaye, Philippe Leray:
Graphical Event Model Learning and Verification for Security Assessment. IEA/AIE 2019: 245-252 - Thierno Kanté, Philippe Leray:
A Probabilistic Relational Model for Risk Assessment and Spatial Resources Management. IEA/AIE 2019: 555-563 - Silja Renooij, Linda C. van der Gaag, Philippe Leray:
On Intercausal Interactions in Probabilistic Relational Models. ISIPTA 2019: 327-329 - 2018
- Marwa El Abri, Philippe Leray, Nadia Essoussi:
DAPER Joint Learning from Partially Structured Graph Databases. ICDEc 2018: 129-138 - Rajani Chulyadyo, Philippe Leray:
Using Probabilistic Relational Models to generate synthetic spatial or non-spatial databases. RCIS 2018: 1-12 - Romain Rincé, Romain Kervarc, Philippe Leray:
Complex Event Processing Under Uncertainty Using Markov Chains, Constraints, and Sampling. RuleML+RR 2018: 147-163 - Linda C. van der Gaag, Philippe Leray:
Qualitative Probabilistic Relational Models. SUM 2018: 276-289 - Jiajun Pan, Hoel Le Capitaine, Philippe Leray:
Relational Constraints for Metric Learning on Relational Data. CoRR abs/1807.00558 (2018) - 2017
- Marwa El Abri, Philippe Leray, Nadia Essoussi:
Learning Probabilistic Relational Models with (Partially Structured) Graph Databases. AICCSA 2017: 256-263 - Youssef Benhaddou, Philippe Leray:
Customer Relationship Management and Small Data - Application of Bayesian Network Elicitation Techniques for Building a Lead Scoring Model. AICCSA 2017: 251-255 - Maroua Haddad, Philippe Leray, Nahla Ben Amor:
Possibilistic MDL: A New Possibilistic Likelihood Based Score Function for Imprecise Data. ECSQARU 2017: 435-445 - Maroua Haddad, Philippe Leray, Amélie Levray, Karim Tabia:
Learning the Parameters of Possibilistic Networks from Data: Empirical Comparison. FLAIRS 2017: 736-741 - Thierno Kanté, Philippe Leray:
A Probabilistic Relational Model Approach for Fault Tree Modeling. IEA/AIE (2) 2017: 154-162 - Romain Rincé, Romain Kervarc, Philippe Leray:
On the Use of WalkSAT Based Algorithms for MLN Inference in Some Realistic Applications. IEA/AIE (2) 2017: 121-131 - Dinh Thuy Phan Huy, Yvan Kokar, Jean Rioult, Nadine Malhouroux-Gaffet, Jean-Christophe Prévotet, Cyril Buey, Philippe Ratajczak, Maryline Hélard, Kammel Rachedi, Abdelwaheb Ourir, Christian Leray, Julien de Rosny, Alain Le Cornec, Azeddine Gati, Thierry Sarrebourse, Patrice Pajusco, Marco Di Renzo:
First Visual Demonstration of Transmit and Receive Spatial Modulations Using the "Radio Wave Display". WSA 2017: 1-7 - 2016
- Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor:
Probabilistic relational model benchmark generation: Principle and application. Intell. Data Anal. 20(3): 615-635 (2016) - Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor:
A Hybrid Approach for Probabilistic Relational Models Structure Learning. IDA 2016: 38-49
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