Inference Optimization
5 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
Input Convex Neural Networks
We show that many existing neural network architectures can be made input-convex with a minor modification, and develop specialized optimization algorithms tailored to this setting.
Iterative Amortized Inference
joelouismarino/iterative_inference
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ICML 2018
The failure of these models to reach fully optimized approximate posterior estimates results in an amortization gap.
A General Method for Amortizing Variational Filtering
joelouismarino/amortized-variational-filtering
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NeurIPS 2018
We introduce the variational filtering EM algorithm, a simple, general-purpose method for performing variational inference in dynamical latent variable models using information from only past and present variables, i. e. filtering.
Easy and Efficient Transformer : Scalable Inference Solution For large NLP model
NetEase-FuXi/EET
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Recently, large-scale transformer-based models have been proven to be effective over a variety of tasks across many domains.
A Novel 1D State Space for Efficient Music Rhythmic Analysis
This paper proposes a new state space approach for music time structure analysis.
