6 citations · 18 across the 11 of their papers we have counts for
18 papers
CostNet: An End-to-End Framework for Goal-Directed Reinforcement Learning
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
Reinforcement Learning (RL) is a general framework concerned with an agent that seeks to maximize rewards in an environment. The learning typically happens through trial and error…
Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook
Morten Goodwin, Kim Tallaksen Halvorsen, Lei Jiao +7
The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These n…
Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing
Saeed Rahimi Gorji, Ole-Christoffer Granmo, Sondre Glimsdal +2
The Tsetlin Machine (TM) is a machine learning algorithm founded on the classical Tsetlin Automaton (TA) and game theory. It further leverages frequent pattern mining and resource…
A Regression Tsetlin Machine with Integer Weighted Clauses for Compact Pattern Representation
K. Darshana Abeyrathna, Ole-Christoffer Granmo, Morten Goodwin
The Regression Tsetlin Machine (RTM) addresses the lack of interpretability impeding state-of-the-art nonlinear regression models. It does this by using conjunctive clauses in prop…
A Tsetlin Machine with Multigranular Clauses
Saeed Rahimi Gorji, Ole-Christoffer Granmo, Adrian Phoulady +1
The recently introduced Tsetlin Machine (TM) has provided competitive pattern recognition accuracy in several benchmarks, however, requires a 3-dimensional hyperparameter search. I…
Environment Sound Classification using Multiple Feature Channels and Attention based Deep Convolutional Neural Network
Jivitesh Sharma, Ole-Christoffer Granmo, Morten Goodwin
In this paper, we propose a model for the Environment Sound Classification Task (ESC) that consists of multiple feature channels given as input to a Deep Convolutional Neural Netwo…