Search Results for author: Jim Torresen

Found 13 papers, 2 papers with code

Adherence Forecasting for Guided Internet-Delivered Cognitive Behavioral Therapy: A Minimally Data-Sensitive Approach

1 code implementation11 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.

Long-Short Ensemble Network for Bipolar Manic-Euthymic State Recognition Based on Wrist-worn Sensors

1 code implementation1 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.

A Model of WiFi Performance With Bounded Latency

no code implementations29 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

Environmental Adaptation of Robot Morphology and Control through Real-world Evolution

no code implementations30 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.

An Interactive Musical Prediction System with Mixture Density Recurrent Neural Networks

no code implementations10 Apr 2019 Charles P. Martin, Jim Torresen

We propose that a mixture density recurrent neural network (MDRNN) is an appropriate model for this task.

Self-Adapting Goals Allow Transfer of Predictive Models to New Tasks

no code implementations4 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

Guiding Neuroevolution with Structural Objectives

no code implementations12 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.

Evolutionary Algorithms

How do Mixture Density RNNs Predict the Future?

no code implementations23 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.

Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing

no code implementations15 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

Deep Predictive Models in Interactive Music

no code implementations31 Jan 2018 Charles P. Martin, Kai Olav Ellefsen, Jim Torresen

Musical performance requires prediction to operate instruments, to perform in groups and to improvise.

Robot Localisation and 3D Position Estimation Using a Free-Moving Camera and Cascaded Convolutional Neural Networks

no code implementations6 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.

Position

RoboJam: A Musical Mixture Density Network for Collaborative Touchscreen Interaction

no code implementations29 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.

BIG-bench Machine Learning

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