5 citations · 11 across the 3 of their papers we have counts for
3 papers
Expressiveness and Learning of Hidden Quantum Markov Models
Sandesh Adhikary, Siddarth Srinivasan, Geoff Gordon +1
Extending classical probabilistic reasoning using the quantum mechanical view of probability has been of recent interest, particularly in the development of hidden quantum Markov m…
Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold
Sandesh Adhikary, Siddarth Srinivasan, Byron Boots
Quantum graphical models (QGMs) extend the classical framework for reasoning about uncertainty by incorporating the quantum mechanical view of probability. Prior work on QGMs has f…
Learning Hidden Quantum Markov Models
Siddarth Srinivasan, Geoff Gordon, Byron Boots
Hidden Quantum Markov Models (HQMMs) can be thought of as quantum probabilistic graphical models that can model sequential data. We extend previous work on HQMMs with three contrib…