Digital Modeling of Reality with Machine Learning
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If you have a question about this talk, please contact jo de bono.
Building digital models of reality and especially visual reality, with all its complexity, is a difficult but exciting task. Many industries, disciplines, and society overall are relying on accurate digital models. The difficulty is amplified by the incomplete, unstructured, and noisy observations we base our models on. We have been working on utilizing, understanding, and improving machine learning techniques to tackle various associated problems to realize accurate digital models of reality. In this talk, I will give a brief summary of our efforts and focus on a few interesting techniques such as interpretability of what we learn and data sampling for effective learning.
This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series.
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