1 code implementation • 28 Oct 2021 • Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong
To this end, we propose Multi-Task Neural Processes (MTNPs), an extension of NPs designed to jointly infer tasks realized from multiple stochastic processes.
no code implementations • ICLR 2022 • Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong
Neural Processes (NPs) consider a task as a function realized from a stochastic process and flexibly adapt to unseen tasks through inference on functions.
1 code implementation • ICLR 2021 • Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
Despite the recent advances in the literature, existing approaches are limited to moderately short-term prediction (less than a few seconds), while extrapolating it to a longer future quickly leads to destruction in structure and content.
2 code implementations • ECCV 2020 • Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee
Despite the simplicity, we show that the proposed method is highly effective, achieving comparable image generation quality to the state-of-the-art methods using the disentangled representation.
2 code implementations • ICLR 2019 • Insu Jeon, Wonkwang Lee, Gunhee Kim
IB-GAN objective is similar to that of InfoGAN but has a crucial difference; a capacity regularization for mutual information is adopted, thanks to which the generator of IB-GAN can harness a latent representation in disentangled and interpretable manner.