research
∙
03/15/2023
Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing
Sparse regression codes (SPARCs) are a promising coding scheme that can ...
share
research
∙
02/07/2023
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise
We study the performance of a Bayesian statistician who estimates a rank...
research
∙
12/03/2022
Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models
We consider the problem of reconstructing the signal and the hidden vari...
research
∙
08/24/2022
Spectrum of non-Hermitian deep-Hebbian neural networks
Neural networks with recurrent asymmetric couplings are important to und...
research
∙
05/20/2022
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation?
We consider the problem of estimating a rank-1 signal corrupted by struc...
research
∙
05/18/2022
Sparse superposition codes with rotational invariant coding matrices for memoryless channels
We recently showed in [1] the superiority of certain structured coding m...
research
∙
02/09/2022
Sparse superposition codes under VAMP decoding with generic rotational invariant coding matrices
Sparse superposition codes were originally proposed as a capacity-achiev...
research
∙
11/06/2019
Statistical physics of unsupervised learning with prior knowledge in neural networks
Integrating sensory inputs with prior beliefs from past experiences in u...
research
∙
04/30/2019