13 citations · 13 across the 1 of their papers we have counts for
6 papers
Physics-informed attention-based neural network for solving non-linear partial differential equations
Ruben Rodriguez-Torrado, Pablo Ruiz, Luis Cueto-Felgueroso +4
Physics-Informed Neural Networks (PINNs) have enabled significant improvements in modelling physical processes described by partial differential equations (PDEs). PINNs are based o…
Bootstrapping Conditional GANs for Video Game Level Generation
Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green +3
Generative Adversarial Networks (GANs) have shown im-pressive results for image generation. However, GANs facechallenges in generating contents with certain types of con-straints,…
Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling
Jiri Navratil, Alan King, Jesus Rios +3
We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based P…
Evolving Agents for the Hanabi 2018 CIG Competition
Rodrigo Canaan, Haotian Shen, Ruben Rodriguez Torrado +3
Hanabi is a cooperative card game with hidden information that has won important awards in the industry and received some recent academic attention. A two-track competition of agen…
Deep Reinforcement Learning for General Video Game AI
Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius +2
The General Video Game AI (GVGAI) competition and its associated software framework provides a way of benchmarking AI algorithms on a large number of games written in a domain-spec…
Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation
Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager +3
Deep reinforcement learning (RL) has shown impressive results in a variety of domains, learning directly from high-dimensional sensory streams. However, when neural networks are tr…