13 citations · 19 across the 7 of their papers we have counts for
9 papers
Views: A Hardware-Aware Recursively Labeled Graph Database Model for Knowledge Representation and Reasoning
Yanjun Yang, Adrian Wheeldon, Yihan Pan +2
Knowledge representation remains a central challenge for reasoning-centered artificial intelligence, particularly when semantic structures involve relations over relations, context…
Runtime Tunable Tsetlin Machines for Edge Inference on eFPGAs
Tousif Rahman, Gang Mao, Bob Pattison +5
Embedded Field-Programmable Gate Arrays (eFPGAs) allow for the design of hardware accelerators of edge Machine Learning (ML) applications at a lower power budget compared with trad…
An Energy-efficient Capacitive-RRAM Content Addressable Memory
Yihan Pan, Adrian Wheeldon, Mohammed Mughal +3
Content addressable memory is popular in intelligent computing systems as it allows parallel content-searching in memory. Emerging CAMs show a promising increase in bitcell density…
An FPGA Architecture for Online Learning using the Tsetlin Machine
Samuel Prescott, Adrian Wheeldon, Rishad Shafik +3
There is a need for machine learning models to evolve in unsupervised circumstances. New classifications may be introduced, unexpected faults may occur, or the initial dataset may…
Energy-frugal and Interpretable AI Hardware Design using Learning Automata
Rishad Shafik, Tousif Rahman, Adrian Wheeldon +2
Energy efficiency is a crucial requirement for enabling powerful artificial intelligence applications at the microedge. Hardware acceleration with frugal architectural allocation i…
Self-timed Reinforcement Learning using Tsetlin Machine
Adrian Wheeldon, Alex Yakovlev, Rishad Shafik
We present a hardware design for the learning datapath of the Tsetlin machine algorithm, along with a latency analysis of the inference datapath. In order to generate a low energy…