no code implementations • 15 Mar 2024 • Tom F. Hansen, Georg H. Erharter, Zhongqiang Liu, Jim Torresen
This study aims to automate the translation of MWD data into actionable metrics for rock engineering.
1 code implementation • 11 Jan 2022 • Ulysse Côté-Allard, Minh H. Pham, Alexandra K. Schultz, Tine Nordgreen, Jim Torresen
This study demonstrates that automatic adherence forecasting for G-ICBT, is achievable using only minimally sensitive data, thus facilitating the implementation of such tools within real-world IDPT platforms.
1 code implementation • 1 Jul 2021 • Ulysse Côté-Allard, Petter Jakobsen, Andrea Stautland, Tine Nordgreen, Ole Bernt Fasmer, Ketil Joachim Oedegaard, Jim Torresen
Manic episodes of bipolar disorder can lead to uncritical behaviour and delusional psychosis, often with destructive consequences for those affected and their surroundings.
no code implementations • 29 Jan 2021 • Bjørn Ivar Teigen, Neil Davies, Kai Olav Ellefsen, Tor Skeie, Jim Torresen
Instead of computing throughput numbers from a steady-state analysis of a Markov chain, we explicitly model latency and packet loss.
Networking and Internet Architecture Performance C.2.2; C.2.5; C.4
no code implementations • 30 Mar 2020 • Tønnes F. Nygaard, Charles P. Martin, David Howard, Jim Torresen, Kyrre Glette
We find that the evolutionary search finds high-performing and diverse morphology-controller configurations by adapting both control and body to the different properties of the physical environments.
no code implementations • 10 Apr 2019 • Charles P. Martin, Jim Torresen
We propose that a mixture density recurrent neural network (MDRNN) is an appropriate model for this task.
no code implementations • 4 Apr 2019 • Kai Olav Ellefsen, Jim Torresen
In this paper, we extend a recent deep learning architecture which learns a predictive model of the environment that aims to predict only the value of a few key measurements, which are be indicative of an agent's performance.
Model-based Reinforcement Learning reinforcement-learning +1
no code implementations • 12 Feb 2019 • Kai Olav Ellefsen, Joost Huizinga, Jim Torresen
However, on a problem where the optimal decomposition is less obvious, the structural diversity objective is found to outcompete other structural objectives -- and this technique can even increase performance on problems without any decomposable structure at all.
no code implementations • 23 Jan 2019 • Kai Olav Ellefsen, Charles Patrick Martin, Jim Torresen
Gaining a better understanding of how and what machine learning systems learn is important to increase confidence in their decisions and catalyze further research.
no code implementations • 15 Mar 2018 • Tønnes F. Nygaard, Charles P. Martin, Jim Torresen, Kyrre Glette
This allows active adaptation of morphology to different environments, and enables rapid tests of morphology with a single robot.
Robotics
no code implementations • 31 Jan 2018 • Charles P. Martin, Kai Olav Ellefsen, Jim Torresen
Musical performance requires prediction to operate instruments, to perform in groups and to improvise.
no code implementations • 6 Jan 2018 • Justinas Miseikis, Patrick Knobelreiter, Inka Brijacak, Saeed Yahyanejad, Kyrre Glette, Ole Jakob Elle, Jim Torresen
This can be the case when sensors and the robot are calibrated in relation to each other and often the reconfiguration of the system is not possible, or extra manual work is required.
no code implementations • 29 Nov 2017 • Charles P. Martin, Jim Torresen
RoboJam is a machine-learning system for generating music that assists users of a touchscreen music app by performing responses to their short improvisations.