collaborators

15 papers

cs.CR2026

Leveraging Interpretable Tsetlin Machine for PDF Malware Detection

Rahul Jaiswal, Ole-Christoffer Granmo

In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents due to its platform independence and ric…

cs.CR2026

On-Device Interpretable Tsetlin Machine-Based Intrusion Detection for Secure IoMT

Rahul Jaiswal, Per-Arne Andersen, Linga Reddy Cenkeramaddi +2

The rapid evolution of digital health technologies is redefining healthcare services worldwide. The integration of wireless communication and Internet-enabled medical devices withi…

cs.LG2026

FastOmniTMAE: Parallel Clause Learning for Scalable and Hardware-Efficient Tsetlin Embeddings

Ahmed K. Kadhim, Lei Jiao, Rishad Shafik +2

Embedding models in natural language processing (NLP) increasingly rely on deep architectures such as BERT, while simpler models such as Word2Vec provide efficient representations…

cs.LG2026

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs

Ole-Christoffer Granmo, Youmna Abdelwahab, Per-Arne Andersen +12

Pattern recognition with concise and flat AND-rules makes the Tsetlin Machine (TM) both interpretable and efficient, while the power of Tsetlin automata enables accuracy comparable…

cs.CR2026

A Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security

Rahul Jaiswal, Per-Arne Andersen, Linga Reddy Cenkeramaddi +2

The rapid adoption of the Internet of Medical Things (IoMT) is transforming healthcare by enabling seamless connectivity among medical devices, systems, and services. However, it a…

eess.SP2026

Explainable and Hardware-Efficient Jamming Detection for 5G Networks Using the Convolutional Tsetlin Machine

Vojtech Halenka, Mohammadreza Amini, Per-Arne Andersen +2

All applications in fifth-generation (5G) networks rely on stable radio-frequency (RF) environments to support mission-critical services in mobility, automation, and connected inte…