In connection with some problems that arise in the study of neural networks random matrices are considered and the probability for them to have certain rank is investigated. Two models are studied in a simple-minded approach to problems of this type
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
This paper focuses on large neural networks whose synaptic connectivity matrices are randomly chosen...
Abstract. In the present paper, the neural networks theory based on presumptions of the Ising model ...
In connection with some problems that arise in the study of neural networks random matrices are cons...
International audienceThis article provides a theoretical analysis of the asymptotic performance of ...
Random Neural Networks (RNNs) area classof Neural Networks (NNs) that can also be seen as a specific...
This paper considers several aspects of random matrix universality in deep neural networks. Motivate...
Abstract. A class of neuralmodels isintroduced inwhichthe topology of the neural network has been ge...
We study the distribution of singular values of product of random matrices pertinent to the analysis...
International audienceRandom Neural Networks (RNNs) are a class of Neural Networks (NNs) that can al...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
International audienceThis article proposes an original approach to the performance understanding of...
International audienceThis article studies the Gram random matrix model G = 1 T Σ T Σ, Σ = σ(W X), c...
In recent publications, a new neural network model, called the random network, has been introduced,...
Random feature mapping (RFM) is the core operation in the random weight neural network (RWNN). Its q...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
This paper focuses on large neural networks whose synaptic connectivity matrices are randomly chosen...
Abstract. In the present paper, the neural networks theory based on presumptions of the Ising model ...
In connection with some problems that arise in the study of neural networks random matrices are cons...
International audienceThis article provides a theoretical analysis of the asymptotic performance of ...
Random Neural Networks (RNNs) area classof Neural Networks (NNs) that can also be seen as a specific...
This paper considers several aspects of random matrix universality in deep neural networks. Motivate...
Abstract. A class of neuralmodels isintroduced inwhichthe topology of the neural network has been ge...
We study the distribution of singular values of product of random matrices pertinent to the analysis...
International audienceRandom Neural Networks (RNNs) are a class of Neural Networks (NNs) that can al...
This book presents a unified theory of random matrices for applications in machine learning, offerin...
International audienceThis article proposes an original approach to the performance understanding of...
International audienceThis article studies the Gram random matrix model G = 1 T Σ T Σ, Σ = σ(W X), c...
In recent publications, a new neural network model, called the random network, has been introduced,...
Random feature mapping (RFM) is the core operation in the random weight neural network (RWNN). Its q...
Providing a broad but in-depth introduction to neural network and machine learning in a statistical ...
This paper focuses on large neural networks whose synaptic connectivity matrices are randomly chosen...
Abstract. In the present paper, the neural networks theory based on presumptions of the Ising model ...
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