NeuralSequenceModels
–Neural Information Processing Systems
All of the questions posed in Table 1in the main paper can be decomposed into readily available components that our modelpθ can estimate. Q1 P (X1) is already naturally in a form that our model can directly estimate due to the autoregressive factorization imposed by the architecture:p θ(X1). Q3 The "hitting time" or the next occurrence of a specific event typea V is defined asτ(a). Interestingly, we can see thatQ3 is a generalization ofQ2 by noting that they are identical when A={}. In practice, computing this exactly is intractable due to it being an infinite sum.
Neural Information Processing Systems
Feb-10-2026, 21:38:25 GMT
- Country:
- Asia > China (0.04)
- North America > United States
- Massachusetts > Middlesex County > Cambridge (0.04)
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