Simone Rossi - RankMe

27 papers A* 5A 1Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning. AABI Zhe Huang, Simone Rossi, Rui Yuan, Thomas Hannagan
2025	J	`jnl`	From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning. CoRR Zhe Huang, Simone Rossi, Rui Yuan, Thomas Hannagan
2025	J	`jnl`	Scaling Laws for Uncertainty in Deep Learning. CoRR Mattia Rosso, Simone Rossi, Giulio Franzese, Markus Heinonen, Maurizio Filippone
2025	J	`jnl`	The Initialization Determines Whether In-Context Learning Is Gradient Descent. CoRR Shifeng Xie, Rui Yuan, Simone Rossi, Thomas Hannagan
2025	J	`jnl`	The Initialization Determines Whether In-Context Learning Is Gradient Descent. Trans. Mach. Learn. Res. Shifeng Xie, Rui Yuan, Simone Rossi, Thomas Hannagan
2025	J	`jnl`	Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL. CoRR Simone Papicchio, Simone Rossi, Luca Cagliero, Paolo Papotti
2024	—	`conf`	Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation. ECCV (29) Yixiao Wang, Chen Tang, Lingfeng Sun, Simone Rossi, Yichen Xie, Chensheng Peng, Thomas Hannagan, Stefano Sabatini, Nicola Poerio, Masayoshi Tomizuka, Wei Zhan
2024	J	`jnl`	Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation. CoRR Yixiao Wang, Chen Tang, Lingfeng Sun, Simone Rossi, Yichen Xie, Chensheng Peng, Thomas Hannagan, Stefano Sabatini, Nicola Poerio, Masayoshi Tomizuka, Wei Zhan
2023	J	`jnl`	Class Balanced Dynamic Acquisition for Domain Adaptive Semantic Segmentation using Active Learning. CoRR Marc Schachtsiek, Simone Rossi, Thomas Hannagan
2023	A*	`conf`	Continuous-Time Functional Diffusion Processes. NeurIPS Giulio Franzese, Giulio Corallo, Simone Rossi, Markus Heinonen, Maurizio Filippone, Pietro Michiardi
2023	J	`jnl`	Continuous-Time Functional Diffusion Processes. CoRR Giulio Franzese, Simone Rossi, Dario Rossi, Markus Heinonen, Maurizio Filippone, Pietro Michiardi
2023	J	`jnl`	How Much Is Enough? A Study on Diffusion Times in Score-Based Generative Models. Entropy Giulio Franzese, Simone Rossi, Lixuan Yang, Alessandro Finamore, Dario Rossi, Maurizio Filippone, Pietro Michiardi
2023	A*	`conf`	On permutation symmetries in Bayesian neural network posteriors: a variational perspective. NeurIPS Simone Rossi, Ankit Singh, Thomas Hannagan
2023	J	`jnl`	On permutation symmetries in Bayesian neural network posteriors: a variational perspective. CoRR Simone Rossi, Ankit Singh, Thomas Hannagan
2022	J	`jnl`	All You Need is a Good Functional Prior for Bayesian Deep Learning. J. Mach. Learn. Res. Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone
2022	J	`jnl`	How Much is Enough? A Study on Diffusion Times in Score-based Generative Models. CoRR Giulio Franzese, Simone Rossi, Lixuan Yang, Alessandro Finamore, Dario Rossi, Maurizio Filippone, Pietro Michiardi
2022	—	`—`	Improving Scalability and Inference in Probabilistic Deep Models. (Avancements dans la scalabilité et l'inférence des modèles profonds probabilistes). Simone Rossi
2021	A*	`conf`	Model Selection for Bayesian Autoencoders. NeurIPS Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Pietro Michiardi, Edwin V. Bonilla, Maurizio Filippone
2021	J	`jnl`	Model Selection for Bayesian Autoencoders. CoRR Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Pietro Michiardi, Edwin V. Bonilla, Maurizio Filippone
2021	A	`conf`	Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations. AISTATS Simone Rossi, Markus Heinonen, Edwin V. Bonilla, Zheyang Shen, Maurizio Filippone
2020	J	`jnl`	All You Need is a Good Functional Prior for Bayesian Deep Learning. CoRR Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone
2020	J	`jnl`	Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations. CoRR Simone Rossi, Markus Heinonen, Edwin V. Bonilla, Zheyang Shen, Maurizio Filippone
2020	A*	`conf`	Walsh-Hadamard Variational Inference for Bayesian Deep Learning. NeurIPS Simone Rossi, Sébastien Marmin, Maurizio Filippone
2019	J	`jnl`	Efficient Approximate Inference with Walsh-Hadamard Variational Inference. CoRR Simone Rossi, Sébastien Marmin, Maurizio Filippone
2019	A*	`conf`	Good Initializations of Variational Bayes for Deep Models. ICML Simone Rossi, Pietro Michiardi, Maurizio Filippone
2019	J	`jnl`	Walsh-Hadamard Variational Inference for Bayesian Deep Learning. CoRR Simone Rossi, Sébastien Marmin, Maurizio Filippone
2018	J	`jnl`	Good Initializations of Variational Bayes for Deep Models. CoRR Simone Rossi, Pietro Michiardi, Maurizio Filippone