no code implementations • 6 Mar 2024 • Cristian Meo, Ankush Roy, Mircea Lică, Junzhe Yin, Zeineb Bou Che, Yanbo Wang, Ruben Imhoff, Remko Uijlenhoet, Justin Dauwels
This paper presents an innovative approach to extreme precipitation nowcasting by employing Transformer-based generative models, namely NowcastingGPT with Extreme Value Loss (EVL) regularization.
no code implementations • 26 Dec 2023 • Hang Chen, Yuchuan Jang, Weijie Zhou, Cristian Meo, Ziwei Chen, Dianbo Liu
Individuals, despite having varied life experiences and learning processes, can communicate effectively through languages.
no code implementations • 8 Apr 2023 • Cristian Meo, Anirudh Goyal, Justin Dauwels
We show that the proposed model is able to uncover OOD generative factors on different datasets and outperforms on average the related baselines in terms of downstream disentanglement metrics.
2 code implementations • 4 Oct 2022 • Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
We formalize the notions of coordination level and heterogeneity level of an environment and present HECOGrid, a suite of multi-agent RL environments that facilitates empirical evaluation of different MARL approaches across different levels of coordination and environmental heterogeneity by providing a quantitative control over coordination and heterogeneity levels of the environment.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 21 May 2022 • Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
In Multi-Agent Reinforcement Learning (MARL), specialized channels are often introduced that allow agents to communicate directly with one another.
Intelligent Communication Multi-agent Reinforcement Learning +2
1 code implementation • 13 Dec 2021 • Cristian Meo, Giovanni Franzese, Corrado Pezzato, Max Spahn, Pablo Lanillos
Adaptation to external and internal changes is major for robotic systems in uncertain environments.
no code implementations • 3 Dec 2021 • Pablo Lanillos, Cristian Meo, Corrado Pezzato, Ajith Anil Meera, Mohamed Baioumy, Wataru Ohata, Alexander Tschantz, Beren Millidge, Martijn Wisse, Christopher L. Buckley, Jun Tani
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning.
1 code implementation • 7 Mar 2021 • Cristian Meo, Pablo Lanillos
Active inference, a theoretical construct inspired by brain processing, is a promising alternative to control artificial agents.