Fei Sha
@feishaai.bsky.social
Scientist and engineer in ai/ml
Http://feisha.org
Http://feisha.org
While o3’s performance is impressive, it is interesting to ask the question: what are the design purposes of setting these benchmarks? And are we making the progress towards the original purposes?
December 23, 2024 at 4:09 PM
While o3’s performance is impressive, it is interesting to ask the question: what are the design purposes of setting these benchmarks? And are we making the progress towards the original purposes?
In modeling 3D turbulent flows of complex dynamical systems, generative models give amazingly accurate results of computing statistical solutions.
We also prove on analytically tractable (toy) models why regression methods to match trajectories is less effective.
arxiv.org/abs/2409.18359
We also prove on analytically tractable (toy) models why regression methods to match trajectories is less effective.
arxiv.org/abs/2409.18359
Generative AI for fast and accurate Statistical Computation of Fluids
We present a generative AI algorithm for addressing the challenging task of fast, accurate and robust statistical computation of three-dimensional turbulent fluid flows. Our algorithm, termed as GenCF...
arxiv.org
December 22, 2024 at 12:16 AM
In modeling 3D turbulent flows of complex dynamical systems, generative models give amazingly accurate results of computing statistical solutions.
We also prove on analytically tractable (toy) models why regression methods to match trajectories is less effective.
arxiv.org/abs/2409.18359
We also prove on analytically tractable (toy) models why regression methods to match trajectories is less effective.
arxiv.org/abs/2409.18359
How transportation of measures can be used for statistical downscaling, ie, from low-resolution to high-resolution while they are samples from two different manifolds?
Our latest work arxiv.org/abs/2412.08079 describes a latent-variable modeling based two-stage approach.
Our latest work arxiv.org/abs/2412.08079 describes a latent-variable modeling based two-stage approach.
Statistical Downscaling via High-Dimensional Distribution Matching with Generative Models
Statistical downscaling is a technique used in climate modeling to increase the resolution of climate simulations. High-resolution climate information is essential for various high-impact applications...
arxiv.org
December 21, 2024 at 11:58 PM
How transportation of measures can be used for statistical downscaling, ie, from low-resolution to high-resolution while they are samples from two different manifolds?
Our latest work arxiv.org/abs/2412.08079 describes a latent-variable modeling based two-stage approach.
Our latest work arxiv.org/abs/2412.08079 describes a latent-variable modeling based two-stage approach.