74 citations · 228 across the 19 of their papers we have counts for
5 papers · 1 filter
Qutrit-inspired Fully Self-supervised Shallow Quantum Learning Network for Brain Tumor Segmentation
Debanjan Konar, Siddhartha Bhattacharyya, Bijaya K. Panigrahi +1
Classical self-supervised networks suffer from convergence problems and reduced segmentation accuracy due to forceful termination. Qubits or bi-level quantum bits often describe qu…
A non-algorithmic approach to "programming" quantum computers via machine learning
Nathan Thompson, James Steck, Elizabeth Behrman
Major obstacles remain to the implementation of macroscopic quantum computing: hardware problems of noise, decoherence, and scaling; software problems of error correction; and, mos…
A Quantum Annealing Approach for Dynamic Multi-Depot Capacitated Vehicle Routing Problem
Ramkumar Harikrishnakumar, Saideep Nannapaneni, Nam H. Nguyen +2
Quantum annealing (QA) is a quantum computing algorithm that works on the principle of Adiabatic Quantum Computation (AQC), and it has shown significant computational advantages in…
Experimental evaluation of quantum Bayesian networks on IBM QX hardware
Sima E. Borujeni, Nam H. Nguyen, Saideep Nannapaneni +2
Bayesian Networks (BN) are probabilistic graphical models that are widely used for uncertainty modeling, stochastic prediction and probabilistic inference. A Quantum Bayesian Netwo…
Quantum circuit representation of Bayesian networks
Sima E. Borujeni, Saideep Nannapaneni, Nam H. Nguyen +2
Probabilistic graphical models such as Bayesian networks are widely used to model stochastic systems to perform various types of analysis such as probabilistic prediction, risk ana…