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Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...

Cash transfers are a popular strategy for reducing poverty and improving health and education outcomes in poor communities. The idea is simple – money is provided to households either without any ...

Abstract: Computationally modelling the affective content of images has been extensively studied recently because of its wide applications in entertainment, advertisement, and education. Significant ...

Probabilities can be written as fractions, decimals or percentages on a scale from 0 to 1. Knowing basic facts about equally likely outcomes can help to solve more complicated problems. Probability is ...

To calculate the probability of an event, the total number of possible outcomes is often required. For simple situations, making a list or completing a sample space diagram is enough but in more ...

Gerolamo Cardano (1501-1576) wrote the first recorded definition of probability. Mlodinow (2009) paraphrased a modernized definition of probability from Cardano's work, Book on Games of Chance: ...

TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of ...

In our recent paper, we propose VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. Several recent end-to-end text-to-speech (TTS) models enabling single ...

WPA quantifies the percent change in a team's chances of winning from one event to the next. It does so by measuring the importance of a given plate appearance in the context of the game. For instance ...