| Clip-forge: Towards zero-shot text-to-shape generation A Sanghi, H Chu, JG Lambourne, Y Wang, CY Cheng, M Fumero, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 266 | 2022 |
| Relative representations enable zero-shot latent space communication L Moschella, V Maiorca, M Fumero, A Norelli, F Locatello, E Rodolà Proc. of The Eleventh International Conference on Learning Representations …, 2022 | 59 | 2022 |
| Learning disentangled representations via product manifold projection M Fumero, L Cosmo, S Melzi, E Rodolà Proceedings of the 38th International Conference on Machine Learning, PMLR …, 2021 | 23 | 2021 |
| Asif: Coupled data turns unimodal models to multimodal without training A Norelli, M Fumero, V Maiorca, L Moschella, E Rodola, F Locatello Advances in Neural Information Processing Systems 36, 15303-15319, 2023 | 20 | 2023 |
| Nonlinear spectral geometry processing via the tv transform M Fumero, M Möller, E Rodolà ACM Transactions on Graphics (TOG) 39 (6), 1-16, 2020 | 12 | 2020 |
| Leveraging sparse and shared feature activations for disentangled representation learning M Fumero, F Wenzel, L Zancato, A Achille, E Rodolà, S Soatto, ... Advances in Neural Information Processing Systems 36, 27682-27698, 2023 | 9 | 2023 |
| A parametric analysis of discrete Hamiltonian functional maps E Postolache, M Fumero, L Cosmo, E Rodola Computer Graphics Forum 39 (5), 103-118, 2020 | 8 | 2020 |
| Certification of Gaussian Boson Sampling via graphs feature vectors and kernels T Giordani, V Mannucci, N Spagnolo, M Fumero, A Rampini, E Rodola, ... Quantum Science and Technology 8 (1), 015005, 2022 | 6 | 2022 |
| Latent space translation via semantic alignment V Maiorca, L Moschella, A Norelli, M Fumero, F Locatello, E Rodolà Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication I Cannistraci, L Moschella, M Fumero, V Maiorca, E Rodolà Proc. of The Twelfth International Conference on Learning Representations …, 2023 | 3 | 2023 |
| Unsupervised source separation via Bayesian inference in the latent domain M Mancusi, E Postolache, G Mariani, M Fumero, A Santilli, L Cosmo, ... arXiv preprint arXiv:2110.05313, 2021 | 2 | 2021 |
| : Cycle-Consistent Multi-Model Merging D Crisostomi, M Fumero, D Baieri, F Bernard, E Rodolà arXiv preprint arXiv:2405.17897, 2024 | 1 | 2024 |
| Infusing invariances in neural representations I Cannistraci, M Fumero, L Moschella, V Maiorca, E Rodolà | 1 | 2023 |
| Unifying Causal Representation Learning with the Invariance Principle D Yao, D Rancati, R Cadei, M Fumero, F Locatello arXiv preprint arXiv:2409.02772, 2024 | | 2024 |
| Latent Space Translation via Inverse Relative Projection V Maiorca, L Moschella, M Fumero, F Locatello, E Rodolà arXiv preprint arXiv:2406.15057, 2024 | | 2024 |
| Latent Functional Maps M Fumero, M Pegoraro, V Maiorca, F Locatello, E Rodolà arXiv preprint arXiv:2406.14183, 2024 | | 2024 |
| Preface of UniReps: the First Workshop on Unifying Representations in Neural Models M Fumero, E Rodolá, C Domine, F Locatello, K Dziugaite, C Mathilde Proceedings of UniReps: the First Workshop on Unifying Representations in …, 2024 | | 2024 |
| Neural style transfer in three-dimensional shapes H Shayani, M Fumero, A Sanghi US Patent App. 18/149,601, 2023 | | 2023 |
| Generating styles for neural style transfer in three-dimensional shapes H Shayani, M Fumero, A Sanghi US Patent App. 18/149,609, 2023 | | 2023 |
| Training machine learning models to perform neural style transfer in three-dimensional shapes H Shayani, M Fumero, A Sanghi US Patent App. 18/149,605, 2023 | | 2023 |
Emanuele RodolàProfessor of Computer Science, Sapienza University of Rome在 di.uniroma1.it 的电子邮件经过验证
