IEEE

TT@CIM: A Tensor-Train In-Memory-Computing Processor Using Bit-Level-Sparsity Optimization and Variable Precision Quantization

Abstract: Computing-in-memory (CIM) is an attractive approach for energy-efficient deep neural network (DNN) processing, especially for low-power edge devices. However, today’s typical DNNs usually ...
IEEE

Short-Term Load Forecasting and Associated Weather Variables Prediction Using ResNet-LSTM Based Deep Learning

Abstract: Short-term load forecasting is mainly utilized in control centers to explore the changing patterns of consumer loads and predict the load value at a certain time in the future. It is one of ...