Random Understanding

Add caption The variational autoencoder or VAE is a directed graphical generative model which has obtained excellent results and is among the state of the art approaches to generative modeling. It assumes that the data is generated by some random process, involving an unobserved continuous random variable  z.  it is assumed that the  z  is generated from some prior distribution  P_θ(z)  and the data is generated from some condition distribution  P_θ(X|Z) , where  X  represents that data. The  z  is sometimes called the hidden representation of data  X . Like any other autoencoder architecture, it has an encoder and a decoder. The encoder part tries to learn  q_φ(z|x) , which is equivalent to learning hidden representation of data  X  or encoding the  X  into the hidden representation (probabilistic encoder). The decoder part tries to learn  P_θ(X|z)  which decoding the hidden representation to...

Human beings along with many other animals have 5 basic senses: Sight, Hearing, Taste, Smell, and Touch . We also have additional senses like a sense of balance and acceleration , a sense of time , etc. Every single moment the human brain processes information from all these sources and each of these senses affects our decision-making process. During any conversation, movement of lips, facial expression along with sound produced by vocal cord helps us to fully understand the meaning of words pronounced by the speaker. We can even understand words only by seeing the lips movement without any sound. This visual information is not just supplementary but necessary. This was first exemplified in the McGurk effect (McGurk & MacDonald, 1976) where a visual /ga/ with a voiced /ba/ is perceived as /da/ by most subjects. As we want our machine learning models to achieve human-level performance, it is also necessary to enable them to use data from various sources. In machine learning thes...