Publications

Emilio Jorge, Hannes Eriksson, Christos Dimitrakakis, Debabrota Basu, Divya Grover Inferential Induction: Joint Bayesian Estimation of MDPs and Value Functions. Contributed talk at ICBINB Workshop@NeurIPS 2020.

Arman Rahbar, Emilio Jorge, Morteza Haghir Chehreghani, Devdatt Dubhashi Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization. arXiv preprint 2019.

Emilio Jorge, Mikael Kågebäck, Fredrik D. Johansson, Emil Gustavsson Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence. Presented at Deep Reinforcement Learning Workshop at NIPS 2016.

Constantin Cronrath, Emilio Jorge, John Moberg et al. BAgger: A Bayesian Algorithm for Safe and Query-efficient Imitation Learning. Presented at International Conference on Intelligent Robots and Systems (IROS) 2018 workshop on Machine Learning in Robot Motion Planning.

Emilio Jorge, Lucas Brynte, Constantin Cronrath et al. Reinforcement learning in real-time geometry assurance. 51st CIRP Conference on Manufacturing Systems (CIRP CMS 2018).

Presentations

Introduction to Normalizing flows on October 10 2019 at RISE AI, Gothenburg.

Posters

Exploration and uncertainty in generative networks for reinforcement learning PhD project overview poster. Presented at German universities and Max Planck institutes during WASP study trip in October 2019.