Matthia Sabatelli

The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms

Gilles Louppe, Pierre Geurts, Matthia Sabatelli, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead

Marco Wiering, Matthia Sabatelli, Valeriu Codreanu, 2018, ICPRAM.

Deep Quality-Value (DQV) Learning pdf

Gilles Louppe, Pierre Geurts, Marco Wiering, 2019, BNAIC/BENELEARN.

Correlation of significant places with self-reported state of bipolar disorder patients

Oscar Mayora-Ibarra, Agnes Grünerbl, Paul Lukowicz, 2014, 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH).

Improving the Training of Deep Convolutional Neural Networks for Art Classification: from Transfer Learning to Multi-Task Learning

Pierre Geurts, Mike Kestemont, Matthia Sabatelli, 2019 .

On the Transferability of Winning Tickets in Non-Natural Image Datasets pdf

Pierre Geurts, Mike Kestemont, Matthia Sabatelli, 2020, ArXiv.

Deep Transfer Learning for Art Classification Problems

Walter Daelemans, Pierre Geurts, Mike Kestemont, 2018, ECCV Workshops.

Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms pdf

Gilles Louppe, Pierre Geurts, Matthia Sabatelli, 2019, NeurIPS 2019.

A Deep Convolutional Neural Network for Location Recognition and Geometry based Information

Lambert Schomaker, Marco Wiering, Matthia Sabatelli, 2018, ICPRAM.

Forest Fire Control with Learning from Demonstration and Reinforcement Learning

Matthia Sabatelli, Marco A. Wiering, Travis Hammond, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning pdf

Gilles Louppe, Pierre Geurts, Matthia Sabatelli, 2020, ArXiv.

Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain

Walter Daelemans, Pierre Geurts, Mike Kestemont, 2021, Electronic Imaging.

On the Transferability of Winning Tickets in Non-Natural Image Datasets

Pierre Geurts, Mike Kestemont, Matthia Sabatelli, 2020, VISIGRAPP.

On The Transferability of Deep-Q Networks pdf

Pierre Geurts, Matthia Sabatelli, P. Geurts, 2021, ArXiv.

Fractional Transfer Learning for Deep Model-Based Reinforcement Learning pdf

Matthia Sabatelli, Marco A. Wiering, Remo Sasso, 2021, ArXiv.

Advances in Digital Music Iconography: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain

Walter Daelemans, Pierre Geurts, Mike Kestemont, 2021, Digit. Humanit. Q..