A one-step flow matching model using transformer in VAE latent space with non-Gaussian source and auxiliary networks generates accurate high-resolution path-dependent stress fields, achieving 6-7x CPU and ~100x GPU speedup over FEM.
In 2019 IEEE 35th International Conference on Data Engineering (ICDE)
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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TSseek approximates time series as line segments and regex queries as bounding rectangles, then uses a distributed spatial index (TSseek-X) to support efficient exact whole-matching and subsequence-matching queries.
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One-Step Flow Matching for Generative Modeling of Path-Dependent Physical Fields
A one-step flow matching model using transformer in VAE latent space with non-Gaussian source and auxiliary networks generates accurate high-resolution path-dependent stress fields, achieving 6-7x CPU and ~100x GPU speedup over FEM.
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TSseek: Regular Expression-Based Similarity Search for Distributed Time Series Datasets
TSseek approximates time series as line segments and regex queries as bounding rectangles, then uses a distributed spatial index (TSseek-X) to support efficient exact whole-matching and subsequence-matching queries.