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0111 · Feb 201919922001200920172026
3 results for Meta-amortization

CogFormer trains a transformer to estimate parameters across various cognitive models.

problem Difficulty in fitting complex cognitive models and iterating over varying assumptions.
method Meta-amortized framework using a transformer to estimate parameters across multiple models.
result CogFormer accurately estimates parameters across different model families with minimal retraining.

Despite the recent success in probabilistic modeling and their applications, generative models trained using traditional inference techniques struggle to adapt to new distributions, even when the target distribution may be closely related to the ones seen during training. In this work, we present a doubly-amortized var…

2019-02-05abs ↗pdf ↗