
Synthesizing Market Data with Autoregressive Flow Matching
Jane Street researchers used flow-matching diffusion and 'atom smoothing' to create a generative model capable of synthesizing complex, discrete-continuous market data streams.
The generation of artificial training and evaluation data using generative models, game engines, or procedural methods — including virtual environments, sensor simulation, and scenario synthesis for domains like autonomous driving, robotics, and computer vision.

Jane Street researchers used flow-matching diffusion and 'atom smoothing' to create a generative model capable of synthesizing complex, discrete-continuous market data streams.
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