Bayesian Neural Networks
Bayesian Neural Networks (BNNs) are a type of neural network that incorporates Bayesian inference into the training process. BNNs use probability distributions to represent the uncertainty in the weights and biases of the network, allowing for more robust predictions and better generalization to new data. Unlike traditional neural networks, which output a single point estimate, BNNs output a probability distribution over the possible outputs. This allows for more nuanced predictions and the ability to quantify the uncertainty in the model's predictions. BNNs are particularly useful in applications where uncertainty is inherent, such as in medical diagnosis or financial forecasting.
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