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ORCIDBobby He
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2020 – today
- 2024
[c8]Bobby He, Thomas Hofmann:
Simplifying Transformer Blocks. ICLR 2024- [c7]Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann:
Recurrent Distance Filtering for Graph Representation Learning. ICML 2024 - [i10]Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf:
Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends. CoRR abs/2403.07379 (2024) - [i9]Bobby He, Lorenzo Noci, Daniele Paliotta, Imanol Schlag, Thomas Hofmann:
Understanding and Minimising Outlier Features in Neural Network Training. CoRR abs/2405.19279 (2024) - 2023
- [j1]Francisca Vasconcelos, Bobby He, Nalini M. Singh, Yee Whye Teh:
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L. Smith, Yee Whye Teh:
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. ICLR 2023 - [c5]Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Dan Roy:
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. NeurIPS 2023 - [i8]Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L. Smith, Yee Whye Teh:
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. CoRR abs/2302.10322 (2023) - [i7]Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Daniel M. Roy:
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit. CoRR abs/2306.17759 (2023) - [i6]Bobby He, Thomas Hofmann:
Simplifying Transformer Blocks. CoRR abs/2311.01906 (2023) - [i5]Yuhui Ding, Antonio Orvieto, Bobby He, Thomas Hofmann:
Recurrent Distance-Encoding Neural Networks for Graph Representation Learning. CoRR abs/2312.01538 (2023) - 2022
- [c4]Bobby He, Mete Ozay:
Feature Kernel Distillation. ICLR 2022 - [c3]Bobby He, Mete Ozay:
Exploring the Gap between Collapsed & Whitened Features in Self-Supervised Learning. ICML 2022: 8613-8634 - [i4]Francisca Vasconcelos, Bobby He, Nalini M. Singh, Yee Whye Teh:
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography. CoRR abs/2202.10847 (2022) - 2021
- [c2]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. AISTATS 2021: 1324-1332 - [i3]Soufiane Hayou, Bobby He, Gintare Karolina Dziugaite:
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning. CoRR abs/2110.11804 (2021) - 2020
- [c1]Bobby He, Balaji Lakshminarayanan, Yee Whye Teh:
Bayesian Deep Ensembles via the Neural Tangent Kernel. NeurIPS 2020 - [i2]Bobby He, Balaji Lakshminarayanan, Yee Whye Teh:
Bayesian Deep Ensembles via the Neural Tangent Kernel. CoRR abs/2007.05864 (2020) - [i1]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. CoRR abs/2010.12859 (2020)
Coauthor Index
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