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Edouard Yvinec
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Books and Theses
- 2023
- [b1]Edouard Yvinec:
Efficient Neural Networks: Post Training Pruning and Quantization. (Accélération des réseaux de neurones). Sorbonne University, Paris, France, 2023
Journal Articles
- 2024
- [j2]Edouard Yvinec
, Arnaud Dapogny, Kevin Bailly
:
PIPE: Parallelized inference through ensembling of residual quantization expansions. Pattern Recognit. 154: 110571 (2024) - 2023
- [j1]Edouard Yvinec
, Arnaud Dapogny, Matthieu Cord
, Kevin Bailly
:
RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3664-3676 (2023)
Conference and Workshop Papers
- 2024
- [c12]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings. ICLR 2024 - 2023
- [c11]Arnaud Dapogny, Gauthier Tallec, Jules Bonnard, Edouard Yvinec, Kévin Bailly:
RULe: Relocalization-Uniformization-Landmark Estimation Network for Real-Time Face Alignment in Degraded Conditions. FG 2023: 1-8 - [c10]Arnaud Dapogny, Gauthier Tallec, Jules Bonnard, Edouard Yvinec, Kévin Bailly:
Adversarial Deep Multi-Task Learning Using Semantically Orthogonal Spaces and Application to Facial Attributes Prediction. FG 2023: 1-8 - [c9]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Designing Strong Baselines for Ternary Neural Network Quantization through Support and Mass Equalization. ICIP 2023: 540-544 - [c8]Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Fighting Over-Fitting with Quantization for Learning Deep Neural Networks on Noisy Labels. ICIP 2023: 575-579 - [c7]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
PowerQuant: Automorphism Search for Non-Uniform Quantization. ICLR 2023 - [c6]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
REx: Data-Free Residual Quantization Error Expansion. NeurIPS 2023 - [c5]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
SPIQ: Data-Free Per-Channel Static Input Quantization. WACV 2023: 3858-3867 - 2022
- [c4]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding. IJCAI 2022: 1601-1607 - [c3]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance. NeurIPS 2022 - 2021
- [c2]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks. NeurIPS 2021: 20863-20873 - 2020
- [c1]Edouard Yvinec, Arnaud Dapogny, Kévin Bailly
:
DeeSCo: Deep heterogeneous ensemble with Stochastic Combinatory loss for gaze estimation. FG 2020: 146-152
Informal and Other Publications
- 2024
- [i18]Edouard Yvinec, Gabriel Kasser:
SPOT: Text Source Prediction from Originality Score Thresholding. CoRR abs/2405.20505 (2024) - 2023
- [i17]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
PowerQuant: Automorphism Search for Non-Uniform Quantization. CoRR abs/2301.09858 (2023) - [i16]Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Fighting over-fitting with quantization for learning deep neural networks on noisy labels. CoRR abs/2303.11803 (2023) - [i15]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Designing strong baselines for ternary neural network quantization through support and mass equalization. CoRR abs/2306.17442 (2023) - [i14]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
SAfER: Layer-Level Sensitivity Assessment for Efficient and Robust Neural Network Inference. CoRR abs/2308.04753 (2023) - [i13]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search. CoRR abs/2308.05600 (2023) - [i12]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Gradient-Based Post-Training Quantization: Challenging the Status Quo. CoRR abs/2308.07662 (2023) - [i11]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings. CoRR abs/2309.17361 (2023) - [i10]Rémi Ouazan Reboul, Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Archtree: on-the-fly tree-structured exploration for latency-aware pruning of deep neural networks. CoRR abs/2311.10549 (2023) - [i9]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
PIPE : Parallelized Inference Through Post-Training Quantization Ensembling of Residual Expansions. CoRR abs/2311.15806 (2023) - 2022
- [i8]Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
Multi-label Transformer for Action Unit Detection. CoRR abs/2203.12531 (2022) - [i7]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
SPIQ: Data-Free Per-Channel Static Input Quantization. CoRR abs/2203.14642 (2022) - [i6]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
REx: Data-Free Residual Quantization Error Expansion. CoRR abs/2203.14645 (2022) - [i5]Edouard Yvinec, Arnaud Dapogny, Kevin Bailly:
To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding. CoRR abs/2203.14646 (2022) - [i4]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance. CoRR abs/2207.04089 (2022) - 2021
- [i3]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks. CoRR abs/2105.14797 (2021) - [i2]Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly:
RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging. CoRR abs/2110.01397 (2021) - 2020
- [i1]Edouard Yvinec, Arnaud Dapogny, Kévin Bailly:
DeeSCo: Deep heterogeneous ensemble with Stochastic Combinatory loss for gaze estimation. CoRR abs/2004.07098 (2020)
Coauthor Index
aka: Kévin Bailly
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