GMRF MCVAE embeds Gaussian Markov Random Fields into VAE prior and posterior distributions to explicitly model cross-component relationships, reporting SOTA results on a synthetic Copula dataset and improved coherence on BIKED.
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MCAC computes exact average and worst-case error metrics for approximate circuits from a single miter using CNF-to-tree conversion and message passing, with reported speedups over standard approaches.
STERN uses factor graphs to unify modeling of trajectory estimation and relative navigation for AUV proximity operations, demonstrated on long-distance acoustic homing to a moving mothership with simulated and real datasets.
citing papers explorer
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Multi-Component VAE with Gaussian Markov Random Field
GMRF MCVAE embeds Gaussian Markov Random Fields into VAE prior and posterior distributions to explicitly model cross-component relationships, reporting SOTA results on a synthetic Copula dataset and improved coherence on BIKED.
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MCAC: A Model Counting Algorithm for Exact Computation of Error Metrics of Approximate Circuits
MCAC computes exact average and worst-case error metrics for approximate circuits from a single miter using CNF-to-tree conversion and message passing, with reported speedups over standard approaches.
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STERN: Simultaneous Trajectory Estimation and Relative Navigation for Autonomous Underwater Proximity Operations
STERN uses factor graphs to unify modeling of trajectory estimation and relative navigation for AUV proximity operations, demonstrated on long-distance acoustic homing to a moving mothership with simulated and real datasets.