Zobrazeno 1 - 10
of 561
pro vyhledávání: '"van der Smagt P"'
In offline reinforcement learning, a policy is learned using a static dataset in the absence of costly feedback from the environment. In contrast to the online setting, only using static datasets poses additional challenges, such as policies generati
Externí odkaz:
http://arxiv.org/abs/2411.04562
Autor:
Gyöngyössy, Natabara Máté, Török, Bernát, Farkas, Csilla, Lucaj, Laura, Menyhárd, Attila, Menyhárd-Balázs, Krisztina, Simonyi, András, van der Smagt, Patrick, Ződi, Zsolt, Lőrincz, András
Regulatory frameworks for the use of AI are emerging. However, they trail behind the fast-evolving malicious AI technologies that can quickly cause lasting societal damage. In response, we introduce a pioneering Assistive AI framework designed to enh
Externí odkaz:
http://arxiv.org/abs/2410.14353
The Finite Element Method (FEM) is a widely used technique for simulating crash scenarios with high accuracy and reliability. To reduce the significant computational costs associated with FEM, the Finite Element Method Integrated Networks (FEMIN) fra
Externí odkaz:
http://arxiv.org/abs/2409.17758
Most recent successes in robot reinforcement learning involve learning a specialized single-task agent. However, robots capable of performing multiple tasks can be much more valuable in real-world applications. Multi-task reinforcement learning can b
Externí odkaz:
http://arxiv.org/abs/2407.13466
Robotic manipulation requires accurate motion and physical interaction control. However, current robot learning approaches focus on motion-centric action spaces that do not explicitly give the policy control over the interaction. In this paper, we di
Externí odkaz:
http://arxiv.org/abs/2407.02904
Autor:
Benbouzid, Djalel, Plociennik, Christiane, Lucaj, Laura, Maftei, Mihai, Merget, Iris, Burchardt, Aljoscha, Hauer, Marc P., Naceri, Abdeldjallil, van der Smagt, Patrick
The growing adoption and deployment of Machine Learning (ML) systems came with its share of ethical incidents and societal concerns. It also unveiled the necessity to properly audit these systems in light of ethical principles. For such a novel type
Externí odkaz:
http://arxiv.org/abs/2405.13191
Incorporating the successful paradigm of pretraining and finetuning from Computer Vision and Natural Language Processing into decision-making has become increasingly popular in recent years. In this paper, we study Imitation Learning from Observation
Externí odkaz:
http://arxiv.org/abs/2404.18896
Autor:
Li, Yin, Chen, Qi, Wang, Kai, Li, Meige, Si, Liping, Guo, Yingwei, Xiong, Yu, Wang, Qixing, Qin, Yang, Xu, Ling, van der Smagt, Patrick, Tang, Jun, Chen, Nutan
Multi-modality magnetic resonance imaging data with various sequences facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC). The lack of publicly available, comprehensive datasets
Externí odkaz:
http://arxiv.org/abs/2404.03253
Autor:
Chen, Nutan, Cseke, Botond, Aljalbout, Elie, Paraschos, Alexandros, Alles, Marvin, van der Smagt, Patrick
We present a novel motion generation approach for robot arms, with high degrees of freedom, in complex settings that can adapt online to obstacles or new via points. Learning from Demonstration facilitates rapid adaptation to new tasks and optimizes
Externí odkaz:
http://arxiv.org/abs/2403.15239
Autor:
Li, Yin, Xiong, Yu, Fan, Wenxin, Wang, Kai, Yu, Qingqing, Si, Liping, van der Smagt, Patrick, Tang, Jun, Chen, Nutan
Objective: Subcutaneous Immunotherapy (SCIT) is the long-lasting causal treatment of allergic rhinitis (AR). How to enhance the adherence of patients to maximize the benefit of allergen immunotherapy (AIT) plays a crucial role in the management of AI
Externí odkaz:
http://arxiv.org/abs/2401.11447