Publications

K. Kassab, A. Schnepf, J.-Y. Franceschi, L. Caraffa, F. Vasile, J. Mary, A. Comport, V. Gouet-Brunet. “Fused-Planes: Improving Planar Representations for Learning Large Sets of 3D Scenes”. In: International Conference on Learning Representations. 2026.

I. Sebag, M. S. Pydi, J.-Y. Franceschi, A. Rakotomamonjy, M. Gartrell, J. Atif, A. Allauzen. “Differentially Private Gradient Flow based on the Sliced Wasserstein Distance”. In: Transactions on Machine Learning Research. 2025.

A. Schnepf, K. Kassab, J.-Y. Franceschi, L. Caraffa, F. Vasile, J. Mary, A. Comport, V. Gouet-Brunet. “Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder”. In: International Conference on Learning Representations. 2025.

K. Kassab, A. Schnepf, J.-Y. Franceschi, L. Caraffa, J. Mary, V. Gouet-Brunet. “RefinedFields: Radiance Fields Refinement for Planar Scene Representations”. In: Transactions on Machine Learning Research. 2025.

T. Issenhuth, S. Lee, L. Dos Santos, J.-Y. Franceschi, C. Kim, A. Rakotomamonjy. “Improving Consistency Models with Generator-Augmented Flows”. In: Proceedings of the 42nd International Conference on Machine Learning. Vol. 267. Proceedings of Machine Learning Research: PMLR, July 2025, pp. 26586–26610.

I. Sebag, J.-Y. Franceschi, A. Rakotomamonjy, A. Allauzen, J. Atif. “On the MIA Vulnerability Gap Between Private GANs and Diffusion Models”. arXiv:2509.03341. Preprint.

M. Vladimirova, J.-Y. Franceschi, T. Issenhuth. “Fairness in Generative AI is Understudied, Underachieved, Undervalued”. HAL:05318171. Preprint.

A. Schnepf, K. Kassab, J.-Y. Franceschi, L. Caraffa, F. Vasile, J. Mary, A. Comport, V. Gouet-Brunet. “Exploring 3D-aware Latent Spaces for Efficiently Learning Numerous Scenes”. arXiv:2403.11678. Accepted to the 3DMV CVPR 2024 workshop.

K. Kassab, A. Schnepf, J.-Y. Franceschi, L. Caraffa, F. Vasile, J. Mary, A. Comport, V. Gouet-Brunet. “Fused-Planes: Improving Planar Representations for Learning Large Sets of 3D Scenes”. arXiv:2410.23742. Preprint.

Y. Yin, M. Kirchmeyer, J.-Y. Franceschi, A. Rakotomamonjy, P. Gallinari. “Continuous PDE Dynamics Forecasting with Implicit Neural Representations”. In: International Conference on Learning Representations. 2023.

J.-Y. Franceschi, M. Gartrell, L. Dos Santos, T. Issenhuth, E. de Bézenac, M. Chen, A. Rakotomamonjy. “Unifying GANs and Score-Based Diffusion as Generative Particle Models”. In: Advances in Neural Information Processing Systems 36. Curran Associates, Inc., 2023, pp. 59729–59760.

J.-Y. Franceschi, E. de Bézenac, I. Ayed, M. Chen, S. Lamprier, P. Gallinari. “A Neural Tangent Kernel Perspective of GANs”. In: Proceedings of the 39th International Conference on Machine Learning. Vol. 162. Proceedings of Machine Learning Research. Baltimore, MD, USA: PMLR, July 2022, pp. 6660–6704.

J. Donà, J.-Y. Franceschi, S. Lamprier, P. Gallinari. “PDE-Driven Spatiotemporal Disentanglement”. In: International Conference on Learning Representations. 2021.

J.-Y. Franceschi, E. Delasalles, M. Chen, S. Lamprier, P. Gallinari. “Stochastic Latent Residual Video Prediction”. In: Proceedings of the 37th International Conference on Machine Learning. Vol. 119. Proceedings of Machine Learning Research. Virtual: PMLR, July 2020, pp. 3233–3246.

J.-Y. Franceschi, A. Dieuleveut, M. Jaggi. “Unsupervised Scalable Representation Learning for Multivariate Time Series”. In: Advances in Neural Information Processing Systems 32. Curran Associates, Inc., 2019, pp. 4650–4661.

J.-Y. Franceschi, A. Fawzi, O. Fawzi. “Robustness of classifiers to uniform ℓ_p and Gaussian noise”. In: Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS). Vol. 84. Proceedings of Machine Learning Research. Playa Blanca, Lanzarote, Canary Islands: PMLR, Apr. 2018, pp. 1280–1288.

A.G.M. Ahmed, J. Guo, D.M. Yan, J.-Y. Franceschi, X. Zhang, O. Deussen. “A Simple Push-Pull Algorithm for Blue-Noise Sampling”. In: IEEE Transactions on Visualization and Computer Graphics 23.12 (Dec. 2017), pp. 2496–2508.