21 citations · 39 across the 8 of their papers we have counts for
14 papers
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…
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
Bimal Bhattarai, Ole-Christoffer Granmo, Lei Jiao
The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as Politi…
Word-level Human Interpretable Scoring Mechanism for Novel Text Detection Using Tsetlin Machines
Bimal Bhattarai, Ole-Christoffer Granmo, Lei Jiao
Recent research in novelty detection focuses mainly on document-level classification, employing deep neural networks (DNN). However, the black-box nature of DNNs makes it difficult…
Enhancing Interpretable Clauses Semantically using Pretrained Word Representation
Rohan Kumar Yadav, Lei Jiao, Ole-Christoffer Granmo +1
Tsetlin Machine (TM) is an interpretable pattern recognition algorithm based on propositional logic, which has demonstrated competitive performance in many Natural Language Process…
Arena-Rosnav: Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systems
Linh Kästner, Teham Buiyan, Xinlin Zhao +3
Recently, mobile robots have become important tools in various industries, especially in logistics. Deep reinforcement learning emerged as an alternative planning method to replace…
On the Convergence of Tsetlin Machines for the XOR Operator
Lei Jiao, Xuan Zhang, Ole-Christoffer Granmo +1
The Tsetlin Machine (TM) is a novel machine learning algorithm with several distinct properties, including transparent inference and learning using hardware-near building blocks. A…