| Benchmark analysis of representative deep neural network architectures S Bianco, R Cadene, L Celona, P Napoletano IEEE access 6, 64270-64277, 2018 | 663 | 2018 |
| Mutan: Multimodal tucker fusion for visual question answering H Ben-Younes, R Cadene, M Cord, N Thome Proceedings of the IEEE international conference on computer vision, 2612-2620, 2017 | 543 | 2017 |
| Murel: Multimodal relational reasoning for visual question answering R Cadene, H Ben-Younes, M Cord, N Thome Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 246 | 2019 |
| Rubi: Reducing unimodal biases for visual question answering R Cadene, C Dancette, M Cord, D Parikh Advances in neural information processing systems 32, 2019 | 225 | 2019 |
| Cross-modal retrieval in the cooking context: Learning semantic text-image embeddings M Carvalho, R Cadène, D Picard, L Soulier, N Thome, M Cord The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 173 | 2018 |
| Block: Bilinear superdiagonal fusion for visual question answering and visual relationship detection H Ben-Younes, R Cadene, N Thome, M Cord Proceedings of the AAAI conference on artificial intelligence 33 (01), 8102-8109, 2019 | 161 | 2019 |
| Beyond question-based biases: Assessing multimodal shortcut learning in visual question answering C Dancette, R Cadene, D Teney, M Cord Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 25 | 2021 |
| Look at the variance! efficient black-box explanations with sobol-based sensitivity analysis T Fel, R Cadène, M Chalvidal, M Cord, D Vigouroux, T Serre Advances in Neural Information Processing Systems 34, 26005-26014, 2021 | 24 | 2021 |
| M2cai workflow challenge: convolutional neural networks with time smoothing and hidden Markov model for video frames classification R Cadene, T Robert, N Thome, M Cord arXiv preprint arXiv:1610.05541, 2016 | 22 | 2016 |
| What i cannot predict, i do not understand: A human-centered evaluation framework for explainability methods T Fel, J Colin, R Cadène, T Serre arXiv preprint arXiv:2112.04417, 2021 | 13 | 2021 |
| Same-different conceptualization: a machine vision perspective M Ricci, R Cadène, T Serre Current Opinion in Behavioral Sciences 37, 47-55, 2021 | 12 | 2021 |
| Master's Thesis: Deep Learning for Visual Recognition R Cadène, N Thome, M Cord arXiv preprint arXiv:1610.05567, 2016 | 11 | 2016 |
| How good is your explanation? algorithmic stability measures to assess the quality of explanations for deep neural networks T Fel, D Vigouroux, R Cadène, T Serre Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 10 | 2022 |
| Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis T Fel, M Ducoffe, D Vigouroux, R Cadène, M Capelle, C Nicodème, ... arXiv preprint arXiv:2202.07728, 2022 | 9 | 2022 |
| Understanding the computational demands underlying visual reasoning M Vaishnav, R Cadene, A Alamia, D Linsley, R VanRullen, T Serre Neural Computation 34 (5), 1075-1099, 2022 | 7 | 2022 |
| Images and recipes: Retrieval in the cooking context M Carvalho, R Cadene, D Picard, L Soulier, M Cord 2018 IEEE 34th International Conference on Data Engineering Workshops (ICDEW …, 2018 | 3 | 2018 |
| Xplique: A deep learning explainability toolbox T Fel, L Hervier, D Vigouroux, A Poche, J Plakoo, R Cadene, M Chalvidal, ... arXiv preprint arXiv:2206.04394, 2022 | 2 | 2022 |
| Deep learning and image classification on a medium dataset of cooking recipes R Cadene Online: http://remicadene. com/uploads/summer-internship-2015. pdf, 2015 | 2 | 2015 |
| Deep Multimodal Learning for Vision and Language Processing R Cadène Sorbonne Université, UPMC, 2020 | 1 | 2020 |
| Overcoming statistical shortcuts for open-ended visual counting C Dancette, R Cadene, X Chen, M Cord arXiv preprint arXiv:2006.10079, 2020 | 1 | 2020 |
Matthieu CordProfessor of Computer Science, Sorbonne UniversityПотвърден имейл адрес: sorbonne-universite.fr
