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papers

Publications (23)

cs.CV2022

SPIQ: Data-Free Per-Channel Static Input Quantization

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1

cs.CV2020

DeeSCo: Deep heterogeneous ensemble with Stochastic Combinatory loss for gaze estimation

Edouard Yvinec, Arnaud Dapogny, Kévin Bailly

cs.CL2025

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431

cs.CV2023

SAfER: Layer-Level Sensitivity Assessment for Efficient and Robust Neural Network Inference

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly +1

cs.CV2023

PowerQuant: Automorphism Search for Non-Uniform Quantization

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1

cs.CL2025

Gemma 3 Technical Report

Gemma Team, Aishwarya Kamath, Johan Ferret +209

cs.CV2022

SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1

cs.LG2022

To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.CL2026

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

cs.CV2023

Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.LG2021

RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1

cs.CL2026

Decoupled DiLoCo for Resilient Distributed Pre-training

Arthur Douillard, Keith Rush, Yani Donchev +14

cs.LG2023

NUPES : Non-Uniform Post-Training Quantization via Power Exponent Search

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.CL2024

SPOT: Text Source Prediction from Originality Score Thresholding

Edouard Yvinec, Gabriel Kasser

cs.CV2022

Multi-label Transformer for Action Unit Detection

Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny +1

cs.CV2023

Fighting over-fitting with quantization for learning deep neural networks on noisy labels

Gauthier Tallec, Edouard Yvinec, Arnaud Dapogny +1

cs.LG2023

Gradient-Based Post-Training Quantization: Challenging the Status Quo

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.AI2026

MedGemma Technical Report

Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78

cs.CV2023

Archtree: on-the-fly tree-structured exploration for latency-aware pruning of deep neural networks

Rémi Ouazan Reboul, Edouard Yvinec, Arnaud Dapogny +1

cs.CV2023

Designing strong baselines for ternary neural network quantization through support and mass equalization

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.CV2023

REx: Data-Free Residual Quantization Error Expansion

Edouard Yvinec, Arnaud Dapgony, Matthieu Cord +1

cs.CV2023

PIPE : Parallelized Inference Through Post-Training Quantization Ensembling of Residual Expansions

Edouard Yvinec, Arnaud Dapogny, Kevin Bailly

cs.CV2021

RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks

Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1