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ORCIDGiuseppe Paolo
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2020 – today
- 2024
[j2]Giuseppe Paolo
, Miranda Coninx, Alban Laflaquière, Stéphane Doncieux:
Discovering and Exploiting Sparse Rewards in a Learned Behavior Space. Evol. Comput. 32(3): 275-305 (2024)- [c7]Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko:
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention. ICML 2024 - [c6]Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl:
Position: A Call for Embodied AI. ICML 2024 - [i15]Abdelhakim Benechehab, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Balázs Kégl:
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning. CoRR abs/2402.03146 (2024) - [i14]Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl:
A call for embodied AI. CoRR abs/2402.03824 (2024) - [i13]Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko:
Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention. CoRR abs/2402.10198 (2024) - [i12]Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl:
Zero-shot Model-based Reinforcement Learning using Large Language Models. CoRR abs/2410.11711 (2024) - [i11]Antoine Grosnit, Alexandre Maraval, James Doran, Giuseppe Paolo, Albert Thomas, Refinath Shahul Hameed Nabeezath Beevi, Jonas Gonzalez, Khyati Khandelwal, Ignacio Iacobacci, Abdelhakim Benechehab, Hamza Cherkaoui, Youssef Attia El Hili, Kun Shao, Jianye Hao, Jun Yao, Balázs Kégl, Haitham Bou-Ammar, Jun Wang:
Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level. CoRR abs/2411.03562 (2024) - 2023
- [j1]Adam Gaier, Giuseppe Paolo, Antoine Cully:
Editorial to the "Evolutionary Reinforcement Learning" Special Issue. ACM Trans. Evol. Learn. Optim. 3(3): 9:1-9:2 (2023) - [i10]Abdelhakim Benechehab, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl:
Multi-timestep models for Model-based Reinforcement Learning. CoRR abs/2310.05672 (2023) - 2022
- [i9]Giuseppe Paolo:
Learning in Sparse Rewards settings through Quality-Diversity algorithms. CoRR abs/2203.01027 (2022) - [i8]Giuseppe Paolo, Jonas Gonzalez-Billandon, Albert Thomas, Balázs Kégl:
Guided Safe Shooting: model based reinforcement learning with safety constraints. CoRR abs/2206.09743 (2022) - 2021
- [b1]Giuseppe Paolo:
Learning in Sparse Rewards settings through Quality-Diversity algorithms. (Apprentissage par renforcement dans le cas de récompenses rares avec exploration par algorithmes de Qualité-Diversité et construction autonome d'espace d'état). Sorbonne University, Paris, France, 2021 - [c5]Giuseppe Paolo, Alexandre Coninx, Stéphane Doncieux, Alban Laflaquière:
Sparse reward exploration via novelty search and emitters. GECCO 2021: 154-162 - [i7]Giuseppe Paolo, Alexandre Coninx, Stéphane Doncieux, Alban Laflaquière:
Sparse Reward Exploration via Novelty Search and Emitters. CoRR abs/2102.03140 (2021) - [i6]Giuseppe Paolo, Alexandre Coninx, Alban Laflaquière, Stéphane Doncieux:
Discovering and Exploiting Sparse Rewards in a Learned Behavior Space. CoRR abs/2111.01919 (2021) - 2020
- [c4]Stéphane Doncieux, Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx:
Novelty search makes evolvability inevitable. GECCO 2020: 85-93 - [c3]Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx, Stéphane Doncieux:
Unsupervised Learning and Exploration of Reachable Outcome Space. ICRA 2020: 2379-2385 - [i5]Stéphane Doncieux, Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx:
Novelty Search makes Evolvability Inevitable. CoRR abs/2005.06224 (2020)
2010 – 2019
- 2019
- [i4]Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx, Stéphane Doncieux:
Unsupervised Learning and Exploration of Reachable Outcome Space. CoRR abs/1909.05508 (2019) - 2018
- [c2]Mark Pfeiffer, Giuseppe Paolo, Hannes Sommer, Juan I. Nieto, Roland Siegwart, Cesar Cadena:
A Data-driven Model for Interaction-Aware Pedestrian Motion Prediction in Object Cluttered Environments. ICRA 2018: 1-8 - 2017
- [c1]Lei Tai, Giuseppe Paolo, Ming Liu:
Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation. IROS 2017: 31-36 - [i3]Lei Tai, Giuseppe Paolo, Ming Liu:
Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation. CoRR abs/1703.00420 (2017) - [i2]Giuseppe Paolo, Lei Tai, Ming Liu:
Towards continuous control of flippers for a multi-terrain robot using deep reinforcement learning. CoRR abs/1709.08430 (2017) - [i1]Mark Pfeiffer, Giuseppe Paolo, Hannes Sommer, Juan I. Nieto, Roland Siegwart, Cesar Cadena:
A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments. CoRR abs/1709.08528 (2017)
Coauthor Index
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