Machine Learning, Optimization, Gradient Descent, Reinforcement Learning.
after-the-fact logit. After-the-fact meaning given we already have a sample for b, we can infer the value of the logit that led to the sample b. g is some function which we assume exists and maps the random variable b back to logits ẑ based on θ and a sample v from a uniform distribution. How we’ll