Pascal Frossard

43 papers · 2016–2026 · 11 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🌍 Conference Polyglot (11) 🏃 Academic Marathon (9) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (10)

🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (7) 🗺️ Taxonomy Completionist (49) 🏆 Grand Slam 🤝 Dynamic Duo (12) 👑 Triple Crown 🏆 Keyword Champion (7) ❓ The Questioner 🗃️ Keyword Collector (106) ⚡ Prolific Year (5) 🚀 Conference Pioneer 📈 Trend Setter 💎 Century Club (42) 🔥 Unstoppable (10)

Conferences

CVPR (10) NIPS (8) ICML (7) ICLR (6) AAAI (3) ECCV (3) AISTATS (2) ACL (1) EACL (1) ICCV (1) MICCAI (1)

Top co-authors

Seyed-Mohsen Moosavi-Dezfooli (12) Guillermo Ortiz-Jimenez (9) Alhussein Fawzi (6) Nikolaos Dimitriadis (5) Apostolos Modas (4) Clément Vignac (4) Francois Fleuret (4) Ke Wang (4) Dorina Thanou (3) Mireille El Gheche (3)

Keywords

decision boundary (7) image classification (6) adversarial robustness (5) adversarial attack (4) adversarial example (4) representation learning (3) domain adaptation (3) convolutional neural network (3) neural tangent kernel (3) adversarial perturbation (3) graph alignment (2) graph neural network (2) black-box attack (2) optimal transport (2) deep neural network (2) autonomous driving (2) 3d object detection (2) feature learning (2) adversarial training (2) neural network (2)

Papers

Semantic Document Derendering: SVG Reconstruction via Vision-Language Modeling AAAI 2026 LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging ICLR 2025 DeFoG: Discrete Flow Matching for Graph Generation ICML 2025 How Compositional Generalization and Creativity Improve as Diffusion Models are Trained ICML 2025 Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology MICCAI 2025 Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences ICLR 2025 Causal Temporal Regime Structure Learning AISTATS 2025 A Classification-Guided Approach for Adversarial Attacks against Neural Machine Translation EACL 2024 IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection CVPR 2024 Pi-DUAL: Using privileged information to distinguish clean from noisy labels ICML 2024 Generative Modelling of Structurally Constrained Graphs NIPS 2024 Bures-Wasserstein Means of Graphs AISTATS 2024 Localizing Task Information for Improved Model Merging and Compression ICML 2024 Sequential Representation Learning via Static-Dynamic Conditional Disentanglement ECCV 2024 Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models ICML 2023 SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud AAAI 2023 Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models NIPS 2023 DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications ACL 2023 DiGress: Discrete Denoising diffusion for graph generation ICLR 2023 A Structured Dictionary Perspective on Implicit Neural Representations CVPR 2022 fGOT: Graph Distances Based on Filters and Optimal Transport AAAI 2022 U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search ECCV 2022 PRIME: A Few Primitives Can Boost Robustness to Common Corruptions ECCV 2022 Top-N: Equivariant Set and Graph Generation without Exchangeability ICLR 2022 Fooling Explanations in Text Classifiers ICLR 2022 What can linearized neural networks actually say about generalization? NIPS 2021 Building powerful and equivariant graph neural networks with structural message-passing NIPS 2020 Hold me tight! Influence of discriminative features on deep network boundaries NIPS 2020 Joint Graph-Based Depth Refinement and Normal Estimation CVPR 2020 GeoDA: A Geometric Framework for Black-Box Adversarial Attacks CVPR 2020 Neural Anisotropy Directions NIPS 2020 Robustness via Curvature Regularization, and Vice Versa CVPR 2019 Geometry Aware Convolutional Filters for Omnidirectional Images Representation ICML 2019 SparseFool: A Few Pixels Make a Big Difference CVPR 2019 A Geometry-Inspired Decision-Based Attack ICCV 2019 GOT: An Optimal Transport framework for Graph comparison NIPS 2019 Geometric Robustness of Deep Networks: Analysis and Improvement CVPR 2018 Robustness of Classifiers to Universal Perturbations: A Geometric Perspective ICLR 2018 Empirical Study of the Topology and Geometry of Deep Networks CVPR 2018 Universal Adversarial Perturbations CVPR 2017 Graph-based Isometry Invariant Representation Learning ICML 2017 Robustness of classifiers: from adversarial to random noise NIPS 2016 DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks CVPR 2016