How is the VAE encoder and decoder probabilistic? I think your view is correct, indeed the probabilistic nature of VAEs stems from parametrizing the latent distribution and then sampling from it I would argue that this procedure influences the whole network, making them more capable of generalization but also more prone to noisy reconstruction (often seen in GANs vs VAE comparisons)
What is probabilistic inference? - Cross Validated Is probabilistic inference only applicable in a graphical modelling context? What's the distinction between traditional statistical inference (p-values, confidence intervals, Bayes factors etc ) and probabilistic inference?
What is the importance of probabilistic machine learning? Contemporary machine learning, as a field, requires more familiarity with Bayesian methods and with probabilistic mathematics than does traditional statistics or even the quantitative social sciences, where frequentist statistical methods still dominate Those coming from Physics are less likely to be surprised by the importance of probabilities in ML since quantum physics is so thoroughly
What is the difference between the probabilistic and non-probabilistic . . . A probabilistic approach (such as Random Forest) would yield a probability distribution over a set of classes for each input sample A deterministic approach (such as SVM) does not model the distribution of classes but rather separates the feature space and return the class associated with the space where a sample originates from
Probabilistic vs. other approaches to machine learning On the other hand, from statistical points (probabilistic approach) of view, we may emphasize more on generative models For example, mixture of Gaussian Model, Bayesian Network, etc The book by Murphy "machine learning a probabilistic perspective" may give you a better idea on this branch
Probability model vs statistical model vs stochastic model The term ' Probability Model ' (probabilistic model) is usually an alias for stochastic model References: 1 Using statistical methods to model the fine-tuning of molecular machines and systems Steinar Thorvaldsen, Ola Hossjer [2] Statistics (Point Estimation) - Lecture One Charlotte Wickham - Berkeley
Whats the difference between probability and statistics? The short answer to this I've heard from Persi Diaconis is the following: The problems considered by probability and statistics are inverse to each other In probability theory we consider some underlying process which has some randomness or uncertainty modeled by random variables, and we figure out what happens In statistics we observe something that has happened, and try to figure out what
What exactly is the problem with overconfident predictions? However the ultimate concern is usually accuracy, so why is this seen as such a problem? If I understnad correctly, the softmax of the final layer is just some numbers and has no meaningful probabilistic interpretation anyway?
Is there any difference between Random and Probabilistic? It seems i can't directly say probabilistic and random are identical But this is telling : random experiment is a probabilistic experiment Is there any difference between Random and Probabili
Anomaly detection via hypothesis test in Poisson distribution The number of daily users ordering from an e-commerce can be modeled using a Poisson distribution I want to detect anomalies using some kind of hypothesis test or probabilistic reasoning That is,