Abstract: Flow Matching (FM) is a simulation-free method for learning a continuous, invertible flow that interpolates between two distributions, and in particular generates data from noise. Inspired ...

Abstract: Despite strong performances on many generative tasks, diffusion and flow matching models require a large number of sampling steps to generate high-quality images. This has motivated the ...

Kémy Adé was shocked by the immigration refusal letter she received. In rejecting her permanent residence application, the Immigration Department cited her current job duties, which included wiring ...

Ligand Pro, founded by Skoltech professors and a Skoltech Ph.D. student, has presented Matcha, an AI-powered molecular docking model that performs virtual drug screening 30 times faster than the large ...

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We introduce Quantum Flow Matching (QFM), a deterministic, simulation-free framework for learning continuous state evolutions on the manifold of quantum density matrices. QFM parameterizes a vector ...

This is the implementation repository of Flow Matching for Tabular Data Synthesis paper by Bahrul Ilmi Nasution, Floor Eijkelboom, Mark Elliot, Richard Allmendinger, Christian A. Naesseth This github ...