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Mohamed El Amine Seddik

Soil Moisture Estimation Using Sentinel-1/-2 Imagery Coupled With CycleGAN for Time-Series Gap Filing
2021 · Natalia Efremova, Mohamed El Amine Seddik, et al. · IEEE Transactions on Geoscience and Remote Sensing · 61
Learning More Universal Representations for Transfer-Learning
2019 · Youssef Tamaazousti, Herve Le Borgne, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 61
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Deep Multi-class Adversarial Specularity Removal
2019 · John Lin, Mohamed El Amine Seddik, et al. · Lecture notes in computer science · 42
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Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
2020 · Seddik, Mohamed El Amine, Louart, Cosme, et al. · arXiv (Cornell University) · 23
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Kernel Random Matrices of Large Concentrated Data: the Example of GAN-Generated Images
2019 · Mohamed El Amine Seddik, Mohamed Tamaazousti, et al. · IEEE International Conference on Acoustics Speech and Signal Processing · 12
Generative collaborative networks for single image super-resolution
2019 · Mohamed El Amine Seddik, Mohamed Tamaazousti, et al. · Neurocomputing · 8
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Do Vision and Language Encoders Represent the World Similarly?
2024 · Mayug Maniparambil, Raiymbek Akshulakov, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 7
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A kernel random matrix-based approach for sparse PCA
2019 · Seddik, Mohamed El Amine, Tamaazousti, Mohamed, et al. · HAL · 7
From outage probability to ALOHA MAC layer performance analysis in distributed WSNs
2018 · Mohamed-El-Amine Seddik, Viktor Toldov, et al. · IEEE Wireless Communications and Networking Conference · 6
Node Feature Kernels Increase Graph Convolutional Network Robustness
2021 · Seddik, Mohamed El Amine, Wu, Changmin, et al. · arXiv (Cornell University) · 5
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Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification
2021 · Benzine, Abdallah, Seddik, Mohamed El Amine, et al. · arXiv (Cornell University) · 5
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How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse
2024 · Seddik, Mohamed El Amine, Chen, Suei-Wen, et al. · arXiv (Cornell University) · 4
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SMArtCast: Predicting soil moisture interpolations into the future using Earth observation data in a deep learning framework
2020 · Foley, Conrad James, Vaze, Sagar, et al. · arXiv (Cornell University) · 4
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When Random Tensors meet Random Matrices
2021 · Seddik, Mohamed El Amine, Guillaud, Maxime, et al. · arXiv (Cornell University) · 3
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The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers
2021 · Mohamed El Amine Seddik, Cosme Louart, et al. · International Conference on Artificial Intelligence and Statistics · 3
Falcon2-11B Technical Report
2024 · Malartic, Quentin, Chowdhury, Nilabhra Roy, et al. · arXiv (Cornell University) · 2
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When random tensors meet random matrices
2024 · Mohamed El Amine Seddik, Maxime Guillaud, et al. · The Annals of Applied Probability · 2
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Neural Networks Classify through the Class-Wise Means of Their Representations
2022 · Mohamed El Amine Seddik, Mohamed Tamaazousti · Proceedings of the AAAI Conference on Artificial Intelligence · 2
Lightweight Neural Networks From PCA & LDA Based Distilled Dense Neural Networks
2020 · Mohamed El Amine Seddik, Hassane Essafi, et al. · Proceedings - International Conference on Image Processing · 2
High-dimensional Learning with Noisy Labels
2024 · Firdoussi, Aymane El, Seddik, Mohamed El Amine · arXiv (Cornell University) · 1
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Why Backdooring Neural Networks is so Easy?
2026 · Seddik, Issam, Seddik, Mohamed El Amine · arXiv (Cornell University)
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How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models
2026 · Seddik, Mohamed El Amine · arXiv (Cornell University)
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Falcon-H1R: Pushing the Reasoning Frontiers with a Hybrid Model for Efficient Test-Time Scaling
2026 · Falcon LLM Team, Chaabane, Iheb, et al. · arXiv (Cornell University)
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High-Dimensional Analysis of Bootstrap Ensemble Classifiers
2025 · Tiomoko, Malik, Cherkaoui, Hamza, et al. · arXiv (Cornell University)
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Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
2024 · Firdoussi, Aymane El, Seddik, Mohamed El Amine, et al. · arXiv (Cornell University)
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Works count: 46
Citation count: 260
H-index: 7
I10-index: 5
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