Publications

See my semantic scholar profile page for more details.

Thesis

Designing Deep Generative Models with Symbiotic Composition
Zhisheng Xiao

Conference and Journal Papers

Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model
Zhisheng Xiao, Tian Han
Conference on Neural Information Processing Systems (NeurIPS), 2022 (Oral)

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Codes Project page
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat
International Conference on Learning Representations (ICLR), 2022 (Spotlight)

Two Symmetrized Coordinate Descent Methods Can Be O(n^2) Times Slower Than the Randomized Version
Peijun Xiao, Zhisheng Xiao, and Ruoyu Sun
SIAM Journal on Optimization, 2021

ControlVAE: Tuning, Analytical Properties, and Performance Analysis
Huajie Shao, Zhisheng Xiao, Shuochao Yao, Aston Zhang, Shengzhong Liu, and Tarek Abdelzaher
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021

VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Code
Zhisheng Xiao, Karsten Kreis, Jan Kautz, and Arash Vahdat
International Conference on Learning Representations (ICLR), 2021 (Spotlight)

Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Code
Zhisheng Xiao, Qing Yan, and Yali Amit
Conference on Neural Information Processing Systems (NeurIPS), 2020

Workshop Papers

Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
Zhisheng Xiao, Qing Yan, and Yali Amit
ICML Workshop on Uncertainty & Robustness in Deep Learning, 2021

EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss
Zhisheng Xiao, Qing Yan, and Yali Amit
Energy Based Models Workshop - ICLR, 2021

Improving Sample Quality by Training and Sampling from Latent Energy
Zhisheng Xiao, Qing Yan, and Yali Amit
ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 2020

Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Zhisheng Xiao, Qing Yan, and Yali Amit
ICML Workshop on Uncertainty & Robustness in Deep Learning, 2020 (Spotlight)

Technical Reports

A Method to Model Conditional Distributions with Normalizing Flows
Zhisheng Xiao, Qing Yan, and Yali Amit
Preprint, 2019

Generative Latent Flow
Zhisheng Xiao, Qing Yan, and Yali Amit
Preprint, 2019