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sequence of changing tasks, environments, or objectives while retaining previously acquired skills. It extends conventional reinforcement learning by addressing catastrophic forgetting, knowledge
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sequence of evolving tasks, graphs, or distributions while retaining previously acquired knowledges. Potential application domains include gesture recognition, human activity recognition, energy
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field. Step 2: Complete All Required Fields Fill out the remaining fields in the online application form ( https://jobs.vib.be/apply/137653 ) according to the provided instructions. Step 3: Upload
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all projects you wish to be considered for in this field. Step 2: Complete All Required Fields Fill out the remaining fields in the online application form ( https://jobs.vib.be/apply/137653
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all projects you wish to be considered for in this field. Step 2: Complete All Required Fields Fill out the remaining fields in the online application form ( https://jobs.vib.be/apply/137653
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include: (1) problem statement and motivation, (2) expected novelty/impact, (3) brief approach (models, algorithms, datasets), (4) evaluation plan, and (5) alignment with IDLab research on reinforcement
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Researcher to support research and development within the SEDAN group ( https://www.uni.lu/snt-en/research-groups/sedan ). The ideal candidate will have expertise or a strong interest in artificial
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will be achieved through the use of freeform optics , enabling the integration of multiple optical functionalities into a single optical surface while ensuring efficient beam shaping and light
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methods that can support decision-making and control in complex industrial systems while balancing multiple, often competing objectives. Industrial processes typically require trade-offs between objectives
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multiple optical channels onto a single sensor) which can address these issues. The goal is to create a flexible toolbox for designing such multi-optics, broadband imaging systems and to develop a