3 citations · 4 across the 15 of their papers we have counts for
7 papers · 1 filter
DeepTTV: Deep Learning Prediction of Hidden Exoplanet From Transit Timing Variations
Chen Chen, Lingkai Kong, Gongjie Li +1
Transit timing variation (TTV) provides rich information about the mass and orbital properties of exoplanets, which are often obtained by solving an inverse problem via Markov Chai…
Quantitative Convergences of Lie Group Momentum Optimizers
Lingkai Kong, Molei Tao
Explicit, momentum-based dynamics that optimize functions defined on Lie groups can be constructed via variational optimization and momentum trivialization. Structure preserving ti…
Quantum State Generation with Structure-Preserving Diffusion Model
Yuchen Zhu, Tianrong Chen, Evangelos A. Theodorou +2
This article considers the generative modeling of the (mixed) states of quantum systems, and an approach based on denoising diffusion model is proposed. The key contribution is an…
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Yuchen Zhu, Tianrong Chen, Lingkai Kong +2
The generative modeling of data on manifolds is an important task, for which diffusion models in flat spaces typically need nontrivial adaptations. This article demonstrates how a…
Convergence of Kinetic Langevin Monte Carlo on Lie groups
Lingkai Kong, Molei Tao
Explicit, momentum-based dynamics for optimizing functions defined on Lie groups was recently constructed, based on techniques such as variational optimization and left trivializat…
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Ye He, Kevin Rojas, Molei Tao
This paper considers the problem of sampling from non-logconcave distribution, based on queries of its unnormalized density. It first describes a framework, Denoising Diffusion Mon…
DFU: scale-robust diffusion model for zero-shot super-resolution image generation
Alex Havrilla, Kevin Rojas, Wenjing Liao +1
Diffusion generative models have achieved remarkable success in generating images with a fixed resolution. However, existing models have limited ability to generalize to different…