HDPG: hyperdimensional policy-based reinforcement learning for continuous control. - Yang Ni 001; Mariam Issa; Danny Abraham; Mahdi Imani; Xunzhao Yin; Mohsen Imani (DAC, 2022)

Hyperdimensional Hybrid Learning on End-Edge-Cloud Networks. - Mariam Issa; Sina Shahhosseini; Yang Ni 001; Tianyi Hu; Danny Abraham; Amir M. Rahmani; Nikil D. Dutt; Mohsen Imani (ICCD, 2022)

QHD: A brain-inspired hyperdimensional reinforcement learning algorithm. - Yang Ni 001; Danny Abraham; Mariam Issa; Yeseong Kim; Pietro Mercati; Mohsen Imani (CoRR, 2022)

Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing. - Yang Ni 001; Danny Abraham; Mariam Issa; Yeseong Kim; Pietro Mercati; Mohsen Imani (ACM Great Lakes Symposium on VLSI, 2023)

DotHash: Estimating Set Similarity Metrics for Link Prediction and Document Deduplication. - Igor Nunes; Mike Heddes; Pere Vergés; Danny Abraham; Alexander V. Veidenbaum; Alex Nicolau; Tony Givargis (KDD, 2023)

Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures. - Mike Heddes; Igor Nunes; Pere Vergés; Denis Kleyko; Danny Abraham; Tony Givargis; Alexandru Nicolau; Alexander V. Veidenbaum (J. Mach. Learn. Res., 2023)

Back to the Future: Reversible Runtime Neural Network Pruning for Safe Autonomous Systems. - Danny Abraham; Biswadip Maity; Bryan Donyanavard; Nikil D. Dutt (DATE, 2024)

Dynamic MAC Protocol for Wireless Spectrum Sharing via Hyperdimensional Self-Learning. - Yang Ni 001; Danny Abraham; Mariam Issa; Alejandro Hernández-Cano; Mahdi Imani; Pietro Mercati; Mohsen Imani (IEEE Access, 2024)

Run-Time ROP Attack Detection on Embedded Devices Using Side Channel Power Analysis. - Jinyao Xu; Danny Abraham; Ian G. Harris (IEEE Embed. Syst. Lett., 2024)