| All You Need is a Good Functional Prior for Bayesian Deep Learning BH Tran, S Rossi, D Milios, M Filippone Journal of Machine Learning Research 23 (74), 1-56, 2022 | 75 | 2022 |
| Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations S Rossi, M Heinonen, E Bonilla, Z Shen, M Filippone International Conference on Artificial Intelligence and Statistics, 2021 | 37 | 2021 |
| How Much Is Enough? A Study on Diffusion Times in Score-Based Generative Models G Franzese, S Rossi, L Yang, A Finamore, D Rossi, M Filippone, ... Entropy 25 (4), 633, 2023 | 31 | 2023 |
| Good Initializations of Variational Bayes for Deep Models S Rossi, P Michiardi, M Filippone International Conference on Machine Learning 2019, 5487-5497, 2019 | 29 | 2019 |
| Walsh-Hadamard Variational Inference for Bayesian Deep Learning S Rossi, S Marmin, M Filippone Advances in Neural Information Processing Systems 33, 9674--9686, 2020 | 17 | 2020 |
| Continuous-Time Functional Diffusion Processes G Franzese, G Corallo, S Rossi, M Heinonen, M Filippone, P Michiardi arXiv preprint arXiv:2303.00800, 2023 | 16 | 2023 |
| Model Selection for Bayesian Autoencoders BH Tran, S Rossi, D Milios, P Michiardi, EV Bonilla, M Filippone Advances in Neural Information Processing Systems 34, 2021 | 13 | 2021 |
| Functional Priors for Bayesian Neural Networks through Wasserstein Distance Minimization to Gaussian Processes BH Tran, D Milios, S Rossi, M Filippone 3rd Symposium on Advances in Approximate Bayesian Inference, 2021 | 3 | 2021 |
| On permutation symmetries in Bayesian neural network posteriors: a variational perspective S Rossi, A Singh, T Hannagan Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Efficient Approximate Inference with Walsh-Hadamard Variational Inference S Rossi, S Marmin, M Filippone 4th NeurIPS Workshop on Bayesian Deep Learning, 2019 | 1 | 2019 |
| Accelerating Convolutional Neural Networks with High-Level Synthesis S Rossi Politecnico di Torino, 2018 | 1 | 2018 |
| Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation Y Wang, C Tang, L Sun, S Rossi, Y Xie, C Peng, T Hannagan, S Sabatini, ... arXiv preprint arXiv:2408.00766, 2024 | | 2024 |
| Understanding in-context learning in transformers S Rossi, R Yuan, T Hannagan The Third Blogpost Track at ICLR 2024, 2024 | | 2024 |
| Class Balanced Dynamic Acquisition for Domain Adaptive Semantic Segmentation using Active Learning M Schachtsiek, S Rossi, T Hannagan arXiv preprint arXiv:2311.14146, 2023 | | 2023 |
| Improving Scalability and Inference in Probabilistic Deep Models S Rossi Sorbonne Université, 2022 | | 2022 |
Maurizio FilipponeAssociate Professor - Statistics Program, KAUSTVerified email at kaust.edu.sa
