22 citations · 55 across the 6 of their papers we have counts for
6 papers
Credit Default Prediction with Projected Quantum Feature Models and Ensembles
Andras Ferenczi, Dagen Wang, Mariya Bessonova +8
Accurate prediction of future loan defaults is a critical capability for financial institutions that provide lines of credit. For institutions that issue and manage extensive loan…
Variational Quantum Self-Organizing Map
Amol Deshmukh
We propose a novel quantum neural network architecture for unsupervised learning of classical and quantum data based on the kernelized version of Kohonen's self-organizing map. The…
Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction
Daniel Fry, Amol Deshmukh, Samuel Yen-Chi Chen +2
Quantum reservoir computing is strongly emerging for sequential and time series data prediction in quantum machine learning. We make advancements to the quantum noise-induced reser…
Implementation and Learning of Quantum Hidden Markov Models
Vanio Markov, Vladimir Rastunkov, Amol Deshmukh +2
In this article, we use the theory of quantum channels and open quantum systems to provide an efficient unitary characterization of a class of stochastic generators known as quantu…
Reservoir Computing via Quantum Recurrent Neural Networks
Samuel Yen-Chi Chen, Daniel Fry, Amol Deshmukh +2
Recent developments in quantum computing and machine learning have propelled the interdisciplinary study of quantum machine learning. Sequential modeling is an important task with…
Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection
Christa Zoufal, Ryan V. Mishmash, Nitin Sharma +6
We introduce a variational quantum algorithm to solve unconstrained black box binary optimization problems, i.e., problems in which the objective function is given as black box. Th…