1 citations · 1 across the 11 of their papers we have counts for
6 papers · 1 filter
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang +4
Semi-implicit distributions have shown great promise in variational inference and generative modeling. Hierarchical semi-implicit models, which stack multiple semi-implicit layers,…
PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
Tianyu Xie, Harry Richman, Jiansi Gao +2
Learning informative representations of phylogenetic tree structures is essential for analyzing evolutionary relationships. Classical distance-based methods have been widely used t…
Diffusion-PINN Sampler
Zhekun Shi, Longlin Yu, Tianyu Xie +1
Recent success of diffusion models has inspired a surge of interest in developing sampling techniques using reverse diffusion processes. However, accurately estimating the drift te…
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions
Tianyu Xie, Frederick A. Matsen, Marc A. Suchard +1
Reconstructing the evolutionary history relating a collection of molecular sequences is the main subject of modern Bayesian phylogenetic inference. However, the commonly used Marko…
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie +2
Semi-implicit variational inference (SIVI) extends traditional variational families with semi-implicit distributions defined in a hierarchical manner. Due to the intractable densit…
Reflected Flow Matching
Tianyu Xie, Yu Zhu, Longlin Yu +5
Continuous normalizing flows (CNFs) learn an ordinary differential equation to transform prior samples into data. Flow matching (FM) has recently emerged as a simulation-free appro…