2021/03/05 · In this paper, we propose a novel abstraction method which abstracts a DNN and a dataset into a Bayesian network (BN).
In this paper, we propose a novel abstraction method which abstracts a DNN and a dataset into a Bayesian network (BN). We make use of dimensionality reduction ...
2021/03/05 · This paper proposes a novel abstraction technique for DNNs through Bayesian approximation: we abstract the behaviour of a DNN on a dataset into ...
2021/10/14 · Bibliographic details on Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features.
2021/03/05 · Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features · 1 code implementation • 5 Mar 2021 ...
2021/11/26 · In this paper, we propose a novel abstraction method which abstracts a DNN and a dataset into a Bayesian network (BN). We make use of ...
Analyzing Deep Neural Networks with Symbolic ... Abstraction and symbolic execution of deep neural networks with bayesian approximation of hidden features.
... Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features. CoRR abs/2103.03704 (2021) (Technical Report) ...
The authors introduced a dimensionality reduction tech- nique using feature extraction algorithms to abstract the behaviour of a neural network into a Bayesian ...
The Impact of Document Vectorisation, RAG, and Large Language Models in Financial Services: An insider view of how AI is set to change the way banks work.