BayesOpt Adversarial Attack. - Binxin Ru; Adam D. Cobb; Arno Blaas; Yarin Gal (ICLR, 2020)

A Bayesian Perspective on Training Speed and Model Selection. - Clare Lyle; Lisa Schut; Binxin Ru; Yarin Gal; Mark van der Wilk (NeurIPS, 2020)

Neural Architecture Generator Optimization. - Binxin Ru; Pedro M. Esperança; Fabio Maria Carlucci (CoRR, 2020)

Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search. - Binxin Ru; Clare Lyle; Lisa Schut; Mark van der Wilk; Yarin Gal (CoRR, 2020)

How Powerful are Performance Predictors in Neural Architecture Search? - Colin White; Arber Zela; Binxin Ru; Yang Liu; Frank Hutter (CoRR, 2021)

Adversarial Attacks on Graph Classification via Bayesian Optimisation. - Xingchen Wan; Henry Kenlay; Binxin Ru; Arno Blaas; Michael A. Osborne; Xiaowen Dong 001 (CoRR, 2021)

AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family. - Roy Henha Eyono; Fabio Maria Carlucci; Pedro M. Esperança; Binxin Ru; Philip H. S. Torr (CoRR, 2021)

DARTS without a Validation Set: Optimizing the Marginal Likelihood. - Miroslav Fil; Binxin Ru; Clare Lyle; Yarin Gal (CoRR, 2021)

Learning to Identify Top Elo Ratings: A Dueling Bandits Approach. - Xue Yan; Yali Du 001; Binxin Ru; Jun Wang 012; Haifeng Zhang 002; Xu Chen 017 (AAAI, 2022)

Bayesian Generational Population-Based Training. - Xingchen Wan; Cong Lu; Jack Parker-Holder; Philip J. Ball; Vu Nguyen; Binxin Ru; Michael A. Osborne (AutoML, 2022)

On Redundancy and Diversity in Cell-based Neural Architecture Search. - Xingchen Wan; Binxin Ru; Pedro M. Esperança; Zhenguo Li (ICLR, 2022)

Approximate Neural Architecture Search via Operation Distribution Learning. - Xingchen Wan; Binxin Ru; Pedro M. Esperança; Fabio Maria Carlucci (WACV, 2022)

Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. - Diego Granziol; Binxin Ru; Xiaowen Dong 001; Stefan Zohren; Michael A. Osborne; Stephen J. Roberts (Algorithms, 2022)

Towards Discovering Neural Architectures from Scratch. - Simon Schrodi; Danny Stoll; Binxin Ru; Rhea Sukthanker; Thomas Brox; Frank Hutter (CoRR, 2022)

DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture. - Kaichen Zhou; Lanqing Hong; Shoukang Hu; Fengwei Zhou; Binxin Ru; Jiashi Feng; Zhenguo Li (Trans. Mach. Learn. Res., 2022)

Dynamic Ensemble of Low-Fidelity Experts: Mitigating NAS "Cold-Start". - Junbo Zhao 001; Xuefei Ning; Enshu Liu; Binxin Ru; Zixuan Zhou; Tianchen Zhao; Chen Chen 007; Jiajin Zhang; Qingmin Liao; Yu Wang 002 (AAAI, 2023)

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars. - Simon Schrodi; Danny Stoll; Binxin Ru; Rhea Sukthanker; Thomas Brox; Frank Hutter (NeurIPS, 2023)

Bayesian Optimisation of Functions on Graphs. - Xingchen Wan; Pierre Osselin; Henry Kenlay; Binxin Ru; Michael A. Osborne; Xiaowen Dong 001 (NeurIPS, 2023)

Neural Architecture Search: Insights from 1000 Papers. - Colin White; Mahmoud Safari; Rhea Sukthanker; Binxin Ru; Thomas Elsken; Arber Zela; Debadeepta Dey; Frank Hutter (CoRR, 2023)

Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start". - Junbo Zhao 001; Xuefei Ning; Enshu Liu; Binxin Ru; Zixuan Zhou; Tianchen Zhao; Chen Chen 077; Jiajin Zhang; Qingmin Liao; Yu Wang 002 (CoRR, 2023)

Bayesian Quadrature for Neural Ensemble Search. - Saad Hamid; Xingchen Wan; Martin Jørgensen; Binxin Ru; Michael A. Osborne (Trans. Mach. Learn. Res., 2023)