Strong Stochastic Flow Maps Accepted as NeurIPS 2026 Oral
Niklas_TR · x · 2026-09-25
Strong Stochastic Flow Maps has been accepted as a NeurIPS 2026 Oral. The work, led by Sam McCallum and Zachary Blasingame with collaborators including Alexander Tong and James Foster, proposes learning the stochastic solution path directly rather than a deterministic probability flow.
Paper and code are available on ArXiv and GitHub; the authors say more results on applications and improvements are coming.
Related event: Strong Stochastic Flow Maps accepted as NeurIPS Oral(2 posts)→
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