1.4k citations · 3.6k across the 44 of their papers we have counts for
6 papers · 1 filter
Neural Architecture Search Over a Graph Search Space
Stanisław Jastrzębski, Quentin de Laroussilhe, Mingxing Tan +3
Neural Architecture Search (NAS) enabled the discovery of state-of-the-art architectures in many domains. However, the success of NAS depends on the definition of the search space.…
Self-Supervised GAN to Counter Forgetting
Ting Chen, Xiaohua Zhai, Neil Houlsby
GANs involve training two networks in an adversarial game, where each network's task depends on its adversary. Recently, several works have framed GAN training as an online or cont…
Self-Supervised GANs via Auxiliary Rotation Loss
Ting Chen, Xiaohua Zhai, Marvin Ritter +2
Conditional GANs are at the forefront of natural image synthesis. The main drawback of such models is the necessity for labeled data. In this work we exploit two popular unsupervis…
On Self Modulation for Generative Adversarial Networks
Ting Chen, Mario Lucic, Neil Houlsby +1
Training Generative Adversarial Networks (GANs) is notoriously challenging. We propose and study an architectural modification, self-modulation, which improves GAN performance acro…
Transfer Learning with Neural AutoML
Catherine Wong, Neil Houlsby, Yifeng Lu +1
We reduce the computational cost of Neural AutoML with transfer learning. AutoML relieves human effort by automating the design of ML algorithms. Neural AutoML has become popular f…
Analyzing Language Learned by an Active Question Answering Agent
Christian Buck, Jannis Bulian, Massimiliano Ciaramita +4
We analyze the language learned by an agent trained with reinforcement learning as a component of the ActiveQA system [Buck et al., 2017]. In ActiveQA, question answering is framed…