Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge. - Nitish Satya Murthy; Peter Vrancx; Nathan Laubeuf; Peter Debacker; Francky Catthoor; Marian Verhelst (SEC, 2022)

Quantized Dynamics Models for Hardware-Efficient Control and Planning in Model-Based RL. - Nitish Satya Murthy; Francky Catthoor; Marian Verhelst; Peter Vrancx (PKDD/ECML Workshops (5), 2023)

Adaptive Block-Scaled GeMMs on Vector Processors for DNN Training at the Edge. - Nitish Satya Murthy; Nathan Laubeuf; Debjyoti Bhattacharjee; Francky Catthoor; Marian Verhelst (VLSI-SoC, 2024)

Optimization of block-scaled integer GeMMs for efficient DNN deployment on scalable in-order vector processors. - Nitish Satya Murthy; Francky Catthoor; Marian Verhelst (J. Syst. Archit., 2024)

Efficient Precision-Scalable Hardware for Microscaling (MX) Processing in Robotics Learning. - Stef Cuyckens; Xiaoling Yi; Nitish Satya Murthy; Chao Fang; Marian Verhelst (CoRR, 2025)