T-SNL modifies sequential neural likelihood estimation with truncation to achieve better accuracy, stability, scalability, and amortization for simulation-based inference in state-space models.
& Truccolo, W.Latent state-space models for neural decoding.2014 36th Annual International Conference of the 12 IEEE Engineering in Medicine and Biology Society, 3033–3036
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.CO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Truncated Neural Likelihood Estimation for Simulation-Based Inference in State-Space Models
T-SNL modifies sequential neural likelihood estimation with truncation to achieve better accuracy, stability, scalability, and amortization for simulation-based inference in state-space models.