38 citations · 92 across the 8 of their papers we have counts for
6 papers · 1 filter
Inference by replication in densely connected systems
Juan P Neirotti, David Saad
An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a l…
Inference and Optimization of Real Edges on Sparse Graphs - A Statistical Physics Perspective
K. Y. Michael Wong, D. Saad
Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe approximation and replica method of statistical physics. Equilibrium states of…
Efficient Bayesian Inference for Learning in the Ising Linear Perceptron and Signal Detection in CDMA
Juan P. Neirotti, David Saad
Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in Code Division Multiple Access (CD…
Equilibration through local information exchange in networks
K. Y. Michael Wong, David Saad
We study the equilibrium states of energy functions involving a large set of real variables, defined on the links of sparsely connected networks, and interacting at the network nod…
Weight vs Magnetization Enumerator for Gallager Codes
J. van Mourik, D. Saad, Y. Kabashima
We propose a method to determine the critical noise level for decoding Gallager type low density parity check error correcting codes. The method is based on the magnetization enume…
Dynamics of Learning with Restricted Training Sets II: Tests and Applications
A. C. C. Coolen, D. Saad
We apply a general theory describing the dynamics of supervised learning in layered neural networks in the regime where the size p of the training set is proportional to the number…