4 citations · 6 across the 2 of their papers we have counts for
3 papers
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller +2
Modeling joint probability distributions over sequences has been studied from many perspectives. The physics community developed matrix product states, a tensor-train decomposition…
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…