1 citations · 2 across the 6 of their papers we have counts for
8 papers
Pictura: Perspective-View Self-Play at Scale for Driving
Yuan Yin, Elias Ramzi, Marc Lafon +8
Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observations such as exact poses and v…
CLIPTTA: Robust Contrastive Vision-Language Test-Time Adaptation
Marc Lafon, Gustavo Adolfo Vargas Hakim, Clément Rambour +2
Vision-language models (VLMs) like CLIP exhibit strong zero-shot capabilities but often fail to generalize under distribution shifts. Test-time adaptation (TTA) allows models to up…
ViLU: Learning Vision-Language Uncertainties for Failure Prediction
Marc Lafon, Yannis Karmim, Julio Silva-Rodríguez +6
Reliable Uncertainty Quantification (UQ) and failure prediction remain open challenges for Vision-Language Models (VLMs). We introduce ViLU, a new Vision-Language Uncertainty quant…
Supra-Laplacian Encoding for Transformer on Dynamic Graphs
Yannis Karmim, Marc Lafon, Raphael Fournier S'niehotta +1
Fully connected Graph Transformers (GT) have rapidly become prominent in the static graph community as an alternative to Message-Passing models, which suffer from a lack of express…
GalLoP: Learning Global and Local Prompts for Vision-Language Models
Marc Lafon, Elias Ramzi, Clément Rambour +2
Prompt learning has been widely adopted to efficiently adapt vision-language models (VLMs), e.g. CLIP, for few-shot image classification. Despite their success, most prompt learnin…
Understanding the Double Descent Phenomenon in Deep Learning
Marc Lafon, Alexandre Thomas
Combining empirical risk minimization with capacity control is a classical strategy in machine learning when trying to control the generalization gap and avoid overfitting, as the…
Energy Correction Model in the Feature Space for Out-of-Distribution Detection
Marc Lafon, Clément Rambour, Nicolas Thome
In this work, we study the out-of-distribution (OOD) detection problem through the use of the feature space of a pre-trained deep classifier. We show that learning the density of i…
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
Marc Lafon, Elias Ramzi, Clément Rambour +1
Out-of-distribution (OOD) detection is a critical requirement for the deployment of deep neural networks. This paper introduces the HEAT model, a new post-hoc OOD detection method…