Machine Learning seminar
When: Wed, 13 Mar 2019, 2pm
Where: A226, College Building
Who: Robin Manhaeve, Katholieke Universiteit Leuven, Belgium.
Title: DeepProbLog: Neural Probabilistic Logic Programming
Abstract: We introduce DeepProbLog, a probabilistic logic programming language that incorporates deep learning by means of neural predicates. We show how existing inference and learning techniques can be adapted for the new language. Our experiments demonstrate that DeepProbLog supports both symbolic and subsymbolic representations and inference, 1) program induction, 2) probabilistic (logic) programming, and 3) (deep) learning from examples. To the best of our knowledge, this work is the first to propose a framework where general-purpose neural networks and expressive probabilistic-logical modeling and reasoning are integrated in a way that exploits the full expressiveness and strengths of both worlds and can be trained end-to-end based on examples.
Bio: Robin Manhaeve is a PhD student at the department of Computer Science at the KU Leuven. In 2017, he completed his MSc in Engineering Science: Computer Science at the KU Leuven. He’s currently researching the integration of Deep Learning and Probabilistic Logic Programming under the supervision of Prof. Luc De Raedt and is funded by an SB grant from the Research Foundation – Flanders (FWO).