7 papers
On the Expressive Power and Capacity of Quantum Data Reuploaders
Lord Sen, Shyamapada Mukherjee
Data reuploading---repeatedly encoding classical inputs at multiple layers of a parameterized quantum circuit---is a central mechanism for enhancing the expressivity of quantum neu…
A Quantum Framework for K Coloring of Graphs
Lord Sen, Shyamapada Mukherjee
Graph coloring is a well-known NP-complete problem with applications in scheduling, register allocation, frequency assignment, and network optimization. Quantum computing offers th…
Mapping Networks
Lord Sen, Shyamapada Mukherjee
The escalating parameter counts in modern deep learning models pose a fundamental challenge to efficient training and resolution of overfitting. We address this by introducing the…
A Novel Unified Approach to Deepfake Detection
Lord Sen, Shyamapada Mukherjee
Advancements in the field of AI are increasingly giving rise to various threats, one of the most prominent being the synthesis and misuse of deepfakes. To sustain trust in this dig…
Symmetric Reduction Techniques for Quantum Graph Colouring
Lord Sen, Shyamapada Mukherjee
This paper introduces an efficient quantum computing method for reducing special graphs in the context of the graph coloring problem. The special graphs considered include both sym…
QuIRK: Quantum-Inspired Re-uploading KAN
Vinayak Sharma, Ashish Padhy, Lord Sen +4
Kolmogorov-Arnold Networks or KANs have shown the ability to outperform classical Deep Neural Networks, while using far fewer trainable parameters for regression problems on scient…
Metric Learning with Quantum Feature Spaces
Vinayak Sharma, Ashish Padhy, Sourav Behera +4
The dimensions of Hilbert space give quantum metric learning exponentially many mutually orthogonal states with which to separate classes, but the same exponential dimension…