2 citations · 2 across the 4 of their papers we have counts for
4 papers
TS-HINT: Enhancing Semiconductor Time Series Regression Using Attention Hints From Large Language Model Reasoning
Jonathan Adam Rico, Nagarajan Raghavan, Senthilnath Jayavelu
Existing data-driven methods rely on the extraction of static features from time series to approximate the material removal rate (MRR) of semiconductor manufacturing processes such…
Incremental Multistep Forecasting of Battery Degradation Using Pseudo Targets
Jonathan Adam Rico, Nagarajan Raghavan, Senthilnath Jayavelu
Data-driven models accurately perform early battery prognosis to prevent equipment failure and further safety hazards. Most existing machine learning (ML) models work in offline mo…
Compound Fault Diagnosis for Train Transmission Systems Using Deep Learning with Fourier-enhanced Representation
Jonathan Adam Rico, Nagarajan Raghavan, Senthilnath Jayavelu
Fault diagnosis prevents train disruptions by ensuring the stability and reliability of their transmission systems. Data-driven fault diagnosis models have several advantages over…
Memristive Nanowire Network for Energy Efficient Audio Classification: Pre-Processing-Free Reservoir Computing with Reduced Latency
Akshaya Rajesh, Pavithra Ananthasubramanian, Nagarajan Raghavan +1
Efficient audio feature extraction is critical for low-latency, resource-constrained speech recognition. Conventional preprocessing techniques, such as Mel Spectrogram, Perceptual…