6 citations · 20 across the 7 of their papers we have counts for
7 papers
Generative Learning of Continuous Data by Tensor Networks
Alex Meiburg, Jing Chen, Jacob Miller +3
Beyond their origin in modeling many-body quantum systems, tensor networks have emerged as a promising class of models for solving machine learning problems, notably in unsupervise…
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…
A Fully Tensorized Recurrent Neural Network
Charles C. Onu, Jacob E. Miller, Doina Precup
Recurrent neural networks (RNNs) are powerful tools for sequential modeling, but typically require significant overparameterization and regularization to achieve optimal performanc…
Adaptive Learning of Tensor Network Structures
Meraj Hashemizadeh, Michelle Liu, Jacob Miller +1
Tensor Networks (TN) offer a powerful framework to efficiently represent very high-dimensional objects. TN have recently shown their potential for machine learning applications and…
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…