5 papers
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
The advancements in the field of AI is increasingly giving rise to various threats. One of the most prominent of them is the synthesis and misuse of Deepfakes. To sustain trust in…
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…
QPMeL - Quantum-Aware Classically-Trained Embeddings via Projective Metric Learning
Vinayak Sharma, Ashish Padhy, Sourav Behera +3
Deep metric learning has recently shown extremely promising results in the classical data domain, creating well-separated feature spaces. This idea was also adapted to quantum comp…