Recurrent Neural Networks with flexible Gates using Kernel activation Functions. - Simone Scardapane; Steven Van Vaerenbergh; Danilo Comminiello; Simone Totaro; Aurelio Uncini (MLSP, 2018)

Kafnets: Kernel-based non-parametric activation functions for neural networks. - Simone Scardapane; Steven Van Vaerenbergh; Simone Totaro; Aurelio Uncini (Neural Networks, 2019)

Lifelong Control of Off-grid Microgrid with Model Based Reinforcement Learning. - Simone Totaro; Ioannis Boukas; Anders Jonsson 001; Bertrand Cornélusse (CoRR, 2020)

Hierarchical reinforcement learning for efficient exploration and transfer. - Lorenzo Steccanella; Simone Totaro; Damien Allonsius; Anders Jonsson 001 (CoRR, 2020)

A non-parametric softmax for improving neural attention in time-series forecasting. - Simone Totaro; Amir Hussain 001; Simone Scardapane (Neurocomputing, 2020)

Adaptive Smoothing for Path Integral Control. - Dominik Thalmeier; Hilbert J. Kappen; Simone Totaro; Vicenç Gómez (J. Mach. Learn. Res., 2020)

Fast Stochastic Kalman Gradient Descent for Reinforcement Learning. - Simone Totaro; Anders Jonsson 001 (L4DC, 2021)

SQL Injections and Reinforcement Learning: An Empirical Evaluation of the Role of Action Structure. - Manuel Del Verme; Åvald Åslaugson Sommervoll; László Erdödi; Simone Totaro; Fabio Massimo Zennaro (NordSec, 2021)

A functional mirror ascent view of policy gradient methods with function approximation. - Sharan Vaswani; Olivier Bachem; Simone Totaro; Robert Mueller; Matthieu Geist; Marlos C. Machado; Pablo Samuel Castro; Nicolas Le Roux (CoRR, 2021)

A general class of surrogate functions for stable and efficient reinforcement learning. - Sharan Vaswani; Olivier Bachem; Simone Totaro; Robert Müller; Shivam Garg; Matthieu Geist; Marlos C. Machado; Pablo Samuel Castro; Nicolas Le Roux (AISTATS, 2022)

Hierarchical Representation Learning for Markov Decision Processes. - Lorenzo Steccanella; Simone Totaro; Anders Jonsson 001 (CoLLAs, 2023)