1 code implementation • 15 Jun 2023 • Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar
For masked training, we introduce an asymmetric encoder-decoder architecture consisting of a transformer encoder that operates only on unmasked patches and a lightweight transformer decoder on full patches.
1 code implementation • 24 Nov 2022 • Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
Diffusion models have found widespread adoption in various areas.
1 code implementation • 22 Jun 2022 • Pan Xu, Hongkai Zheng, Eric Mazumdar, Kamyar Azizzadenesheli, Anima Anandkumar
Existing Thompson sampling-based algorithms need to construct a Laplace approximation (i. e., a Gaussian distribution) of the posterior distribution, which is inefficient to sample in high dimensional applications for general covariance matrices.
4 code implementations • 6 Nov 2021 • Zongyi Li, Hongkai Zheng, Nikola Kovachki, David Jin, Haoxuan Chen, Burigede Liu, Kamyar Azizzadenesheli, Anima Anandkumar
Specifically, in PINO, we combine coarse-resolution training data with PDE constraints imposed at a higher resolution.
3 code implementations • ICML 2020 • Florian Schäfer, Hongkai Zheng, Anima Anandkumar
We show that opponent-aware modelling of generator and discriminator, as present in competitive gradient descent (CGD), can significantly strengthen ICR and thus stabilize GAN training without explicit regularization.