1 code implementation • 20 Aug 2023 • Xin Ding, Yongwei Wang, Zuheng Xu
Although Negative Data Augmentation (NDA) effectively enhances unconditional and class-conditional GANs by introducing anomalies into real training images, guiding the GANs away from low-quality outputs, its impact on CcGANs is limited, as it fails to replicate negative samples that may occur during the CcGAN sampling.
2 code implementations • 16 May 2022 • Zuheng Xu, Naitong Chen, Trevor Campbell
This work presents mixed variational flows (MixFlows), a new variational family that consists of a mixture of repeated applications of a map to an initial reference distribution.
1 code implementation • 11 Mar 2022 • Naitong Chen, Zuheng Xu, Trevor Campbell
A Bayesian coreset is a small, weighted subset of data that replaces the full dataset during Bayesian inference, with the goal of reducing computational cost.
1 code implementation • 13 Apr 2021 • Zuheng Xu, Trevor Campbell
Gaussian variational inference and the Laplace approximation are popular alternatives to Markov chain Monte Carlo that formulate Bayesian posterior inference as an optimization problem, enabling the use of simple and scalable stochastic optimization algorithms.
2 code implementations • 7 Apr 2021 • Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch
Knowledge distillation (KD) has been actively studied for image classification tasks in deep learning, aiming to improve the performance of a student based on the knowledge from a teacher.
1 code implementation • NeurIPS 2020 • Dionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell
Standard Bayesian inference algorithms are prohibitively expensive in the regime of modern large-scale data.
1 code implementation • ICLR 2021 • Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang
This work proposes the continuous conditional generative adversarial network (CcGAN), the first generative model for image generation conditional on continuous, scalar conditions (termed regression labels).
Ranked #2 on Image Generation on RC-49