Search Results for author: Ruikang Ouyang

Found 3 papers, 1 papers with code

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers

no code implementations10 Feb 2025 Jiajun He, Yuanqi Du, Francisco Vargas, Dinghuai Zhang, Shreyas Padhy, Ruikang Ouyang, Carla Gomes, José Miguel Hernández-Lobato

We consider the sampling problem, where the aim is to draw samples from a distribution whose density is known only up to a normalization constant.

BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching

no code implementations15 Sep 2024 Ruikang Ouyang, Bo Qiang, Zixing Song, José Miguel Hernández-Lobato

Developing an efficient sampler capable of generating independent and identically distributed (IID) samples from a Boltzmann distribution is a crucial challenge in scientific research, e. g. molecular dynamics.

Denoising

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