Explainability Techniques for Graph Convolutional Networks F Baldassarre, H Azizpour International Conference on Machine Learning (ICML 2019) - Workshop …, 2019 | 175 | 2019 |
Deep koalarization: Image colorization using cnns and inception-resnet-v2 F Baldassarre, DG Morín, L Rodés-Guirao arXiv preprint arXiv:1712.03400, 2017 | 103 | 2017 |
GraphQA: Protein Model Quality Assessment using Graph Convolutional Network F Baldassarre, DM Hurtado, A Elofsson, H Azizpour Bioinformatics Journal, 2020 | 80 | 2020 |
Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks F Baldassarre, K Smith, J Sullivan, H Azizpour European Conference on Computer Vision (ECCV 2020), 2020 | 19 | 2020 |
Towards Self-Supervised Learning of Global and Object-Centric Representations F Baldassarre, H Azizpour ICLR 2022 Workshop on Objects, Structure and Causality, 2022 | 9 | 2022 |
Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors F Baldassarre, Q Debard, GF Pontiveros, TK Wijaya British Machine Vision Conference (BMVC 2022), 2022 | 2 | 2022 |
Learnable masked tokens for improved transferability of self-supervised vision transformers H Hu, F Baldassarre, H Azizpour Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 2 | 2022 |
Variable Rate Allocation for Vector-Quantized Autoencoders F Baldassarre, A El-Nouby, H Jégou ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
Structured Representations for Explainable Deep Learning F Baldassarre KTH Royal Institute of Technology, 2023 | | 2023 |
Morphing architectures for pose-based image generation of people in clothing F Baldassarre KTH - Royal Insitute of Technology (Stockholm, Sweden), 2018 | | 2018 |