Pascal Frossard

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