6 papers
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,…
Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling
Tianyu Xie, Shuchen Xue, Zijin Feng +4
Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a compelling trade-off between quality…
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…
Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
Ziheng Cheng, Tianyu Xie, Shiyue Zhang +1
While conditional diffusion models have achieved remarkable success in various applications, they require abundant data to train from scratch, which is often infeasible in practice…
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…
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
Tianyu Xie, Musu Yuan, Minghua Deng +1
Probability estimation of tree topologies is one of the fundamental tasks in phylogenetic inference. The recently proposed subsplit Bayesian networks (SBNs) provide a powerful prob…