136 citations · 360 across the 45 of their papers we have counts for
4 papers · 1 filter
Programmable Quantum Annealers as Noisy Gibbs Samplers
Marc Vuffray, Carleton Coffrin, Yaroslav A. Kharkov +1
Drawing independent samples from high-dimensional probability distributions represents the major computational bottleneck for modern algorithms, including powerful machine learning…
Monotonicity Properties of Physical Network Flows and Application to Robust Optimal Allocation
Sidhant Misra, Marc Vuffray, Anatoly Zlotnik
We derive conditions for monotonicity properties that characterize general flows of a commodity over a network, where the flow is described by potential and flow dynamics on the ed…
Learning of Discrete Graphical Models with Neural Networks
Abhijith J., Andrey Y. Lokhov, Sidhant Misra +1
Graphical models are widely used in science to represent joint probability distributions with an underlying conditional dependence structure. The inverse problem of learning a disc…
The Impacts of Convex Piecewise Linear Cost Formulations on AC Optimal Power Flow
Carleton Coffrin, Bernard Knueven, Jesse Holzer +1
Despite strong connections through shared application areas, research efforts on power market optimization (e.g., unit commitment) and power network optimization (e.g., optimal pow…