8 citations · 12 across the 6 of their papers we have counts for
3 papers · 1 filter
Out of Distribution Detection, Generalization, and Robustness Triangle with Maximum Probability Theorem
Amir Emad Marvasti, Ehsan Emad Marvasti, Ulas Bagci
Maximum Probability Framework, powered by Maximum Probability Theorem, is a recent theoretical development in artificial intelligence, aiming to formally define probabilistic model…
Maximum Probability Theorem: A Framework for Probabilistic Learning
Amir Emad Marvasti, Ehsan Emad Marvasti, Ulas Bagci +1
We present a theoretical framework of probabilistic learning derived by Maximum Probability (MP) Theorem shown in the current paper. In this probabilistic framework, a model is def…
Rediscovering Deep Neural Networks Through Finite-State Distributions
Amir Emad Marvasti, Ehsan Emad Marvasti, George Atia +1
We propose a new way of thinking about deep neural networks, in which the linear and non-linear components of the network are naturally derived and justified in terms of principles…