47 citations · 94 across the 21 of their papers we have counts for
8 papers · 1 filter
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…
Towards Model-based Reinforcement Learning for Industry-near Environments
Per-Arne Andersen, Morten Goodwin, Ole-Christoffer Granmo
Deep reinforcement learning has over the past few years shown great potential in learning near-optimal control in complex simulated environments with little visible information. Ra…
A Neural Turing~Machine for Conditional Transition Graph Modeling
Mehdi Ben Lazreg, Morten Goodwin, Ole-Christoffer Granmo
Graphs are an essential part of many machine learning problems such as analysis of parse trees, social networks, knowledge graphs, transportation systems, and molecular structures.…
The Regression Tsetlin Machine: A Tsetlin Machine for Continuous Output Problems
K. Darshana Abeyrathna, Ole-Christoffer Granmo, Lei Jiao +1
The recently introduced Tsetlin Machine (TM) has provided competitive pattern classification accuracy in several benchmarks, composing patterns with easy-to-interpret conjunctive c…
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks
K. Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang +1
In this paper, we apply a new promising tool for pattern classification, namely, the Tsetlin Machine (TM), to the field of disease forecasting. The TM is interpretable because it i…
The Convolutional Tsetlin Machine
Ole-Christoffer Granmo, Sondre Glimsdal, Lei Jiao +3
Convolutional neural networks (CNNs) have obtained astounding successes for important pattern recognition tasks, but they suffer from high computational complexity and the lack of…
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation
Erlend Olsvik, Christian M. D. Trinh, Kristian Muri Knausgård +5
Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environm…