7 citations · 10 across the 7 of their papers we have counts for
9 papers
Digital Twin Modeling of Quantum Dynamical Systems: Dissipative Quantum Reservoir Computing
Abhijit Sen, Bikram Keshari Parida, Shital Chauhan +2
Modeling the response of driven many-body quantum systems from input--output data is difficult: the dynamics are nonlinear, history dependent, and expensive to simulate as system s…
K-U-KAN: Koopman-Enhanced U-KAN for 3D Dental Reconstruction from a Single Panoramic X-ray Radiograph
Bikram Keshari Parida, Abhijit Sen, Wonsang You
A panoramic X-ray compresses a 3D jaw into a 2D strip; we aim to recover the missing depth cleanly and fast. Existing implicit neural representations render realistic volumes but a…
From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
Abhijit Sen, Sonali Panda, Mahima Arya +3
This tutorial is designed to make reinforcement learning (RL) more accessible to undergraduate students by offering clear, example-driven explanations. It focuses on bridging the g…
Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints
Abhijit Sen, Illya V. Lukin, Kurt Jacobs +3
The prediction of quantum dynamical responses lies at the heart of modern physics. Yet, modeling these time-dependent behaviors remains a formidable challenge because quantum syste…
Predicting Entanglement Entropy from Particle Tunneling of Interacting Fermions Using Kolmogorov-Arnold Networks
Elvira Bilokon, Valeriia Bilokon, Abhijit Sen +3
Entanglement entropy is a fundamental measure of quantum correlations and a key resource underpinning advances in quantum information and many-body physics. We uncover a universal…
Feature Engineering is Not Dead: Reviving Classical Machine Learning with Entropy, HOG, and LBP Feature Fusion for Image Classification
Abhijit Sen, Giridas Maiti, Bikram K. Parida +3
Feature engineering continues to play a critical role in image classification, particularly when interpretability and computational efficiency are prioritized over deep learning mo…
ViT-NeBLa: A Hybrid Vision Transformer and Neural Beer-Lambert Framework for Single-View 3D Reconstruction of Oral Anatomy from Panoramic Radiographs
Bikram Keshari Parida, Anusree P. Sunilkumar, Abhijit Sen +1
Dental diagnosis relies on two primary imaging modalities: panoramic radiographs (PX) providing 2D oral cavity representations, and Cone-Beam Computed Tomography (CBCT) offering de…
Input-Output Optics as a Causal Time Series Mapping: A Generative Machine Learning Solution
Abhijit Sen, Bikram Keshari Parida, Kurt Jacobs +1
The response of many-body quantum systems to an optical pulse can be extremely challenging to model. Here we explore the use of neural networks, both traditional and generative, to…
Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficent-KAN and WAV-KAN
Subhajit Patra, Sonali Panda, Bikram Keshari Parida +4
Physics-informed neural networks have proven to be a powerful tool for solving differential equations, leveraging the principles of physics to inform the learning process. However,…