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Found 9 papers, 6 papers with code
Anticancer Peptides Classification using Kernel Sparse Representation Classifier
In this paper, we present an intuitive classification strategy that differs from the traditional \emph{black box} method and is based on the well-known statistical theory of \emph{sparse-representation classification} (SRC).
DIBERT: Dependency Injected Bidirectional Encoder Representations from Transformers
Prior research in the area of Natural Language Processing (NLP) has shown that including the syntactic structure of a sentence using a dependency parse tree while training a representation learning model improves the performance on downstream tasks.
Performance Analysis of Fractional Learning Algorithms
Fractional learning algorithms are trending in signal processing and adaptive filtering recently.
Short-Term Load Forecasting using Bi-directional Sequential Models and Feature Engineering for Small Datasets
Electricity load forecasting enables the grid operators to optimally implement the smart grid's most essential features such as demand response and energy efficiency.
AFP-SRC: Identification of Antifreeze Proteins Using Sparse Representation Classifier
In this research, we propose a computational framework for the prediction of AFPs which is essentially based on a sample-specific classification method using the sparse reconstruction.
E3-targetPred: Prediction of E3-Target Proteins Using Deep Latent Space Encoding
Understanding E3 ligase and target substrate interactions are important for cell biology and therapeutic development.
A Mathematical Framework for Deep Learning in Elastic Source Imaging
An inverse elastic source problem with sparse measurements is of concern.
Comments on "Design of fractional-order variants of complex LMS and NLMS algorithms for adaptive channel equalization"
The purpose of this note is to highlight some critical flaws in recently proposed fractional-order variants of complex least mean square (CLMS) and normalized least mean square (NLMS) algorithms in "Design of Fractional-order Variants of Complex LMS and Normalized LMS Algorithms for Adaptive Channel Equalization" [Non-linear Dyn.
Optimization and Control
Deep Learning Diffuse Optical Tomography
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level.
