4 citations · 5 across the 2 of their papers we have counts for
4 papers
Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework
Jacob Miller, Geoffrey Roeder, Tai-Danae Bradley
We investigate a correspondence between two formalisms for discrete probabilistic modeling: probabilistic graphical models (PGMs) and tensor networks (TNs), a powerful modeling fra…
Adaptive Epidemic Forecasting and Community Risk Evaluation of COVID-19
Vishrawas Gopalakrishnan, Sayali Navalekar, Pan Ding +7
Pandemic control measures like lock-down, restrictions on restaurants and gatherings, social-distancing have shown to be effective in curtailing the spread of COVID-19. However, th…
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…
Tensor Networks for Probabilistic Sequence Modeling
Jacob Miller, Guillaume Rabusseau, John Terilla
Tensor networks are a powerful modeling framework developed for computational many-body physics, which have only recently been applied within machine learning. In this work we util…