Understanding Measures of Uncertainty for Adversarial Example Detection. - Lewis Smith; Yarin Gal (UAI, 2018)

Idealised Bayesian Neural Networks Cannot Have Adversarial Examples: Theoretical and Empirical Study. - Yarin Gal; Lewis Smith (CoRR, 2018)

Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning. - Mike Walmsley; Lewis Smith; Chris J. Lintott; Yarin Gal; Steven Bamford; Hugh Dickinson; Lucy Fortson; Sandor Kruk; Karen Masters; Claudia Scarlata; Brooke Simmons; Rebecca J. Smethurst; et al. (CoRR, 2019)

Flood Detection On Low Cost Orbital Hardware. - Gonzalo Mateo-Garcia; Silviu Oprea; Lewis Smith; Josh Veitch-Michaelis; Guy Schumann; Yarin Gal; Atilim Günes Baydin; Dietmar Backes (CoRR, 2019)

A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks. - Angelos Filos; Sebastian Farquhar; Aidan N. Gomez; Tim G. J. Rudner; Zachary Kenton; Lewis Smith; Milad Alizadeh; Arnoud de Kroon; Yarin Gal (CoRR, 2019)

Uncertainty Estimation Using a Single Deep Deterministic Neural Network. - Joost van Amersfoort; Lewis Smith; Yee Whye Teh; Yarin Gal (ICML, 2020)

Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations. - Sebastian Farquhar; Lewis Smith; Yarin Gal (NeurIPS, 2020)

Try Depth Instead of Weight Correlations: Mean-field is a Less Restrictive Assumption for Deeper Networks. - Sebastian Farquhar; Lewis Smith; Yarin Gal (CoRR, 2020)

Simple and Scalable Epistemic Uncertainty Estimation Using a Single Deep Deterministic Neural Network. - Joost van Amersfoort; Lewis Smith; Yee Whye Teh; Yarin Gal (CoRR, 2020)

Capsule Networks - A Probabilistic Perspective. - Lewis Smith; Lisa Schut; Yarin Gal; Mark van der Wilk (CoRR, 2020)

Semi-supervised Learning of Galaxy Morphology using Equivariant Transformer Variational Autoencoders. - Mizu Nishikawa-Toomey; Lewis Smith; Yarin Gal (CoRR, 2020)

Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression. - Joost van Amersfoort; Lewis Smith; Andrew Jesson; Oscar Key; Yarin Gal (CoRR, 2021)

Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. - Lewis Smith; Joost van Amersfoort; Haiwen Huang; Stephen J. Roberts; Yarin Gal (CoRR, 2021)

Quantifying Uncertainty for Machine Learning Based Diagnostic. - Owen Convery; Lewis Smith; Yarin Gal; Adi Hanuka (CoRR, 2021)

Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (NeurIPS, 2024)

Improving Dictionary Learning with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (CoRR, 2024)

Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. - Tom Lieberum; Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Nicolas Sonnerat; Vikrant Varma; János Kramár; Anca D. Dragan; Rohin Shah; Neel Nanda (CoRR, 2024)