Deep directed generative models with energy-based probability estimation.

Monte Carlo (MC) integration is the de facto method for approximating the predictive distribution of Bayesian neural networks (BNNs).

This problem is known as location parameter estimation in the statistics literature.

In reinforcement learning the Q-values summarize the expected future rewards that the agent will attain.

Measuring and making DNA is central to modern biology and biomedicine.

Here, we show that marginal variance tends to increase along the causal order for generically sampled additive noise models.

Here, we show that marginal variance tends to increase along the causal order for generically sampled additive noise models.