Transfer Learning with Neural AutoML

Catherine Wong, Neil Houlsby, Yifeng Lu +1

Experimental Adaptive Bayesian Tomography

Konstantin Kravtsov, Stanislav Straupe, Igor Radchenko +3

Ask the Right Questions: Active Question Reformulation with Reinforcement Learning

Christian Buck, Jannis Bulian, Massimiliano Ciaramita +4

Neural Architecture Search Over a Graph Search Space

Stanisław Jastrzębski, Quentin de Laroussilhe, Mingxing Tan +3

The paper introduces a graph-based representation for neural architecture search spaces, where decisions are vertices and actions are edges, enabling iterative and branching design…

On Self Modulation for Generative Adversarial Networks

Ting Chen, Mario Lucic, Neil Houlsby +1

Parameter-Efficient Transfer Learning for NLP

Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski +5

Self-Supervised GANs via Auxiliary Rotation Loss

Ting Chen, Xiaohua Zhai, Marvin Ritter +2

Bayesian Active Learning for Classification and Preference Learning

Neil Houlsby, Ferenc Huszár, Zoubin Ghahramani +1

Scalable Probabilistic Entity-Topic Modeling

Neil Houlsby, Massimiliano Ciaramita

Analyzing Language Learned by an Active Question Answering Agent

Christian Buck, Jannis Bulian, Massimiliano Ciaramita +4

Self-Supervised GAN to Counter Forgetting

Ting Chen, Xiaohua Zhai, Neil Houlsby