Disentangling Improves VAEs' Robustness to Adversarial Attacks. - Matthew Willetts; Alexander Camuto; Stephen J. Roberts; Chris C. Holmes (CoRR, 2019)

Regularising Deep Networks with DGMs. - Matthew Willetts; Alexander Camuto; Stephen J. Roberts; Chris C. Holmes (CoRR, 2019)

Explicit Regularisation in Gaussian Noise Injections. - Alexander Camuto; Matthew Willetts; Umut Simsekli; Stephen J. Roberts; Chris C. Holmes (NeurIPS, 2020)

Learning Bijective Feature Maps for Linear ICA. - Alexander Camuto; Matthew Willetts; Chris C. Holmes; Brooks Paige; Stephen J. Roberts (AISTATS, 2021)

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. - Alexander Camuto; Matthew Willetts; Stephen J. Roberts; Chris C. Holmes; Tom Rainforth (AISTATS, 2021)

Improving VAEs' Robustness to Adversarial Attack. - Matthew Willetts; Alexander Camuto; Tom Rainforth; Stephen J. Roberts; Christopher C. Holmes (ICLR, 2021)

Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. - Alexander Camuto; Xiaoyu Wang; Lingjiong Zhu; Chris C. Holmes; Mert Gürbüzbalaban; Umut Simsekli (ICML, 2021)

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. - Alexander Camuto; George Deligiannidis; Murat A. Erdogdu; Mert Gürbüzbalaban; Umut Simsekli; Lingjiong Zhu (NeurIPS, 2021)

Certifiably Robust Variational Autoencoders. - Ben Barrett; Alexander Camuto; Matthew Willetts; Tom Rainforth (AISTATS, 2022)

Variational Autoencoders: A Harmonic Perspective. - Alexander Camuto; Matthew Willetts (AISTATS, 2022)

Verifiable evaluations of machine learning models using zkSNARKs. - Tobin South; Alexander Camuto; Shrey Jain; Shayla Nguyen; Robert Mahari; Christian Paquin; Jason Morton; Alex 'Sandy' Pentland (CoRR, 2024)