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Found 4 papers, 3 papers with code
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Noise-contrastive estimation (NCE) is a popular method for estimating unnormalised probabilistic models, such as energy-based models, which are effective for modelling complex data distributions.
MCMC-Correction of Score-Based Diffusion Models for Model Composition
Diffusion models can be parameterised in terms of either a score or an energy function.
Active Learning with Weak Supervision for Gaussian Processes
Annotating data for supervised learning can be costly.
A general framework for ensemble distribution distillation
Ensembles of neural networks have been shown to give better performance than single networks, both in terms of predictions and uncertainty estimation.
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