The Kolmogorov-Arnold Representation Theorem The foundation of KANs lies in the Kolmogorov-Arnold Representation Theorem (KART). This theorem states that any continuous multivariate function can be represented as a superposition of…
This post aims to give a thorough overview of the current state and future prospects of interpretability and explainability in deep learning, making it a valuable resource for students, researchers,…
In this post, I will share my GitHub repository which you may refer to develop your own model. It comprises implementation for training, testing and interpretation. This post will cover…
Publication details The paper is published in the Special Issue of the ECML PKDD 2022 Journal Track - Springer Machine Learning as in 2022: click here Abstract In biomedical image…
Publication details The paper is published in the journal of Springer Machine Vision and Applications in 2022: click here Abstract To automate the process of delineation to highlight or identify…
For any young researcher, this is a dream come true opportunity to be part of HLF. Following my selection in the recent 8th HLF 2021 event, I will share my…
This posts follow from the setup of the master slave cluster using Apache Spark (here) Considering your Spark environment is ready, we can make use of Elephas library to develop…
Biomedical image analysis The success of deep learning in image analysis has encouraged the biomedical imaging researchers to investigate its potential in analyzing various medical modalities to aid clinicians in…
About In this post, I will talk about my experience in attending the International Joint Conference on Neural Networks (IJCNN) 2021 organized by the International Neural Network Society. It is…
What is covered? Types of optimizers and learning ratesKeras callbacks and checkpoints like early stopping, adjusting learning rates, etc. Types of optimizers and adaptive learning methods Optimizers In neural networks…