activity
20122026
most citedAccurate, fully-automated NMR spectral profiling for metabolomics

312 citations · 1.2k across the 54 of their papers we have counts for

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Showing cs.AIShow all

7 papers · 1 filter

cs.AI2022★ 2 cited

Utility Theory for Sequential Decision Making

Mehran Shakerinava, Siamak Ravanbakhsh

The von Neumann-Morgenstern (VNM) utility theorem shows that under certain axioms of rationality, decision-making is reduced to maximizing the expectation of some utility function.…

cs.AI2015★ 1 cited

Message Passing and Combinatorial Optimization

Siamak Ravanbakhsh

Graphical models use the intuitive and well-studied methods of graph theory to implicitly represent dependencies between variables in large systems. They can model the global behav…

cs.AI2014★ 312 cited

Accurate, fully-automated NMR spectral profiling for metabolomics

Siamak Ravanbakhsh, Philip Liu, Trent Bjorndahl +9

Many diseases cause significant changes to the concentrations of small molecules (aka metabolites) that appear in a person's biofluids, which means such diseases can often be readi…

cs.AI2014

Revisiting Algebra and Complexity of Inference in Graphical Models

Siamak Ravanbakhsh, Russell Greiner

This paper studies the form and complexity of inference in graphical models using the abstraction offered by algebraic structures. In particular, we broadly formalize inference pro…

cs.AI2014★ 7 cited

Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning

Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner

The cutting plane method is an augmentative constrained optimization procedure that is often used with continuous-domain optimization techniques such as linear and convex programs.…

cs.AI2014★ 1 cited

Perturbed Message Passing for Constraint Satisfaction Problems

Siamak Ravanbakhsh, Russell Greiner

We introduce an efficient message passing scheme for solving Constraint Satisfaction Problems (CSPs), which uses stochastic perturbation of Belief Propagation (BP) and Survey Propa…

cs.AI2012★ 2 cited

A Generalized Loop Correction Method for Approximate Inference in Graphical Models

Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner

Belief Propagation (BP) is one of the most popular methods for inference in probabilistic graphical models. BP is guaranteed to return the correct answer for tree structures, but c…