Few-shot meta-learning supports rapid adaptation with limited labeled data, but remains sensitive to hyperparameters and support set quality. We propose Uncertainty-Decomposed Reliability-Gated Meta-Learning (UDRML). It selects support sets with low predictive entropy, combines diverse adapted models to estimate aleato...
Mainak Mallick, Seong-geun Shin, Hyuck-kee Lee et al.· Machines· 0 citations
Radar hardware faults threaten automated perception, motivating accurate, compact diagnosis and understandable maintenance guidance. We introduce SCORE-LM, which couples a small scatterer-conditioned operator-response encoder (SCORE) to an adapted local language model. SCORE combines self-referenced complex trajectorie...
DualRes is introduced, a compact oscillatory state-space model that combines two complementary spectral views of vibration, capturing rapid changes and fine frequency structure that supports oscillatory memory as a compact approach to vibration diagnosis under limited labelled exposure.
To maintain high efficiency and reduce operational downtime in industrial manufacturing, effective Predictive Maintenance (PdM) for robotic manipulators is essential. Although combining Model-Agnostic Meta-Learning (MAML) with digital twin technology offers a solid basis for quickly identifying faults, conventional met...
Mainak Mallick, Seung-Kyum Choi· 2026 6th International Confe...· 0 citations
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