Human Activity Classification Using Basic Machine Learning Models. - Bikram Khanal; Pablo Rivas 001; Javier Orduz (CSCI, 2021)

Quantum Machine Learning: A Case Study of Grover's Algorithm. - Bikram Khanal; Pablo Rivas 001; Javier Orduz; Alibek Zhakubayev (CSCI, 2021)

Supercomputing leverages quantum machine learning and Grover's algorithm. - Bikram Khanal; Javier Orduz; Pablo Rivas 001; Erich Baker (J. Supercomput., 2023)

Automated Synthesis of Distributed Code from Sequential Snippets Using Deep Learning. - Arun Sanjel; Bikram Khanal; Pablo Rivas 001; Greg Speegle (IEEE Big Data, 2024)

A Modified Depolarization Approach for Efficient Quantum Machine Learning. - Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

On Adversarial Examples for Text Classification by Perturbing Latent Representations. - Korn Sooksatra; Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

Generalization Error Bound for Quantum Machine Learning in NISQ Era - A Survey. - Bikram Khanal; Pablo Rivas 001; Arun Sanjel; Korn Sooksatra; Ernesto Quevedo; Alejandro Rodríguez Pérez (CoRR, 2024)

Learning Robust Observable to Address Noise in Quantum Machine Learning. - Bikram Khanal; Pablo Rivas 001 (CoRR, 2024)

NLP-Guided Synthesis: Transitioning from Sequential Programs to Distributed Programs. - Arun Sanjel; Bikram Khanal; Greg Speegle; Pablo Rivas 001 (CoRR, 2024)

Quantum-Enhanced Representation Learning: A Quanvolutional Autoencoder Approach against DDoS Threats. - Pablo Rivas 001; Javier Orduz; Tonni Das Jui; Casimer M. DeCusatis; Bikram Khanal (Mach. Learn. Knowl. Extr., 2024)

Generalization error bound for quantum machine learning in NISQ era - a survey. - Bikram Khanal; Pablo Rivas 001; Arun Sanjel; Korn Sooksatra; Ernesto Quevedo; Alejandro Rodriguez (Quantum Mach. Intell., 2024)

Data-dependent generalization bounds for parameterized quantum models under noise. - Bikram Khanal; Pablo Rivas 001 (J. Supercomput., 2025)