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https://youtu.be/ufG0YLj_sik Speaker: Adam Wagner, Tel Aviv University Title: Constructions in combinatorics via neural networks Abstract: Recently, significant progress has been made in the area of machine learning algorithms, and they have quickly become some of the most exciting tools in a scientist’s toolbox. In particular, recent advances in the field of reinforcement learning have led […] |
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https://youtu.be/zJOWdZZcitk Speaker: Thomas Fischbacher, Google Title: New results in Supergravity via ML Technology Abstract: The infrastructure built to power the Machine Learning revolution has many other uses beyond Deep Learning. Starting from a general architecture-level overview over the lower levels of Google’s TensorFlow machine learning library, we review how this has recently helped us to […] |
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https://youtu.be/4wHwqYrCqVQ Speaker: Marijn Heule, Carnegie Mellon University Title: Computer-Aided Mathematics and Satisfiability Abstract: Progress in satisfiability (SAT) solving has made it possible to determine the correctness of complex systems and answer long-standing open questions in mathematics. The SAT solving approach is completely automatic and can produce clever though potentially gigantic proofs. We can have confidence […] |
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https://youtu.be/rRGh97sOtKE Speaker: Patrick Massot, Laboratoire de Mathématiques d’Orsay and CNRS Title: Why explain mathematics to computers? Abstract: A growing number of mathematicians are having fun explaining mathematics to computers using proof assistant softwares. This process is called formalization. In this talk I’ll describe what formalization looks like, what kind of things it teaches us, and […] |
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