Bayesian Deep Ensembles via the Neural Tangent Kernel. - Bobby He; Balaji Lakshminarayanan; Yee Whye Teh (NeurIPS, 2020)

Stable ResNet. - Soufiane Hayou; Eugenio Clerico; Bobby He; George Deligiannidis; Arnaud Doucet; Judith Rousseau (AISTATS, 2021)

Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning. - Soufiane Hayou; Bobby He; Gintare Karolina Dziugaite (CoRR, 2021)

Feature Kernel Distillation. - Bobby He; Mete Ozay (ICLR, 2022)

Exploring the Gap between Collapsed & Whitened Features in Self-Supervised Learning. - Bobby He; Mete Ozay (ICML, 2022)

Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. - Bobby He; James Martens; Guodong Zhang; Aleksandar Botev; Andrew Brock; Samuel L. Smith; Yee Whye Teh (ICLR, 2023)

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. - Lorenzo Noci; Chuning Li; Mufan Bill Li; Bobby He; Thomas Hofmann 001; Chris J. Maddison; Dan Roy (NeurIPS, 2023)

The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. - Lorenzo Noci; Chuning Li; Mufan Bill Li; Bobby He; Thomas Hofmann 001; Chris J. Maddison; Daniel M. Roy 001 (CoRR, 2023)

Recurrent Distance-Encoding Neural Networks for Graph Representation Learning. - Yuhui Ding; Antonio Orvieto; Bobby He; Thomas Hofmann 001 (CoRR, 2023)

UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography. - Francisca Vasconcelos; Bobby He; Nalini M. Singh; Yee Whye Teh (Trans. Mach. Learn. Res., 2023)

Simplifying Transformer Blocks. - Bobby He; Thomas Hofmann 001 (ICLR, 2024)

Recurrent Distance Filtering for Graph Representation Learning. - Yuhui Ding; Antonio Orvieto; Bobby He; Thomas Hofmann 001 (ICML, 2024)

Understanding and Minimising Outlier Features in Transformer Training. - Bobby He; Lorenzo Noci; Daniele Paliotta; Imanol Schlag; Thomas Hofmann 001 (NeurIPS, 2024)

Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. - Sidak Pal Singh; Bobby He; Thomas Hofmann 001; Bernhard Schölkopf (CoRR, 2024)

Understanding and Minimising Outlier Features in Neural Network Training. - Bobby He; Lorenzo Noci; Daniele Paliotta; Imanol Schlag; Thomas Hofmann 001 (CoRR, 2024)

The Directionality of Optimization Trajectories in Neural Networks. - Sidak Pal Singh; Bobby He; Thomas Hofmann 001; Bernhard Schölkopf (ICLR, 2025)