Annotation
This seminar explores the implementation of neural networks within quantum computing frameworks. It begins with a refresher on classical neural networks, followed by an introduction to quantum-inspired soft computing, including the development of a quantum neuron model and the Quantum-Inspired Backpropagation Neural Network (QBPNN) architecture. Key topics include the operational principles of QBPNN, its quantum backpropagation algorithm, and applications for image denoising and deblurring in comparison to classical Multi-Layer Perceptron (MLP) architectures. The talk further delves into the TensorFlow Quantum Framework (TQF), Parameterised Quantum Circuits (PQCs), and Quantum Convolutional Neural Networks (QCNNs). It concludes by highlighting the advantages of Quantum Neural Networks (QNNs) over classical approaches, offering insights into the future of quantum computing in machine learning.
Benefits for the attendees, what they will learn:
The first part of the seminar will introduce quantum-inspired soft computing with reference to building a quantum-inspired multilayer neural network architecture characterised by a sigmoidal activation function and a quantum backpropagation algorithm for adjustment of network interconnections.
The second part will introduce the audience to the philosophy behind gate-based quantum neural networks and their implementation using parameterised quantum circuits.
At the end of the seminar, the attendees will be able to conceptualise the intricacies involved in designing quantum-inspired and quantum neural networks.
Level
Beginner
Language
English
Prerequisites
Background of neural networks.
Fundamentals of quantum computing.
Tutor
Dr. Siddhartha Bhattacharyya is a distinguished researcher and professor specialising in computer science, hybrid intelligence, and quantum computing. He holds multiple degrees in Optics, Optoelectronics, and Computer Science from prestigious institutions in India and Europe, including a PhD from Jadavpur University and a habilitation degree from VSB Technical University of Ostrava. Dr. Bhattacharyya has authored over 400 research publications, co-edited 114 books, and holds multiple patents. He serves as Co-Editor-in-Chief of Applied Soft Computing Journal and Senior Editor of IEEE Access, among other editorial roles. Recognised globally, he has received numerous awards, including the ACM Distinguished Speaker title and the IEEE Computer Society Distinguished Visitor honour. His research focuses on hybrid intelligence, pattern recognition, multimedia data processing, social networks, and quantum computing.
