Modeling Order in Neural Word Embeddings at Scale. - Andrew Trask; David Gilmore; Matthew Russell (ICML, 2015)

sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings. - Andrew Trask; Phil Michalak; John Liu (CoRR, 2015)

Neural Arithmetic Logic Units. - Andrew Trask; Felix Hill; Scott E. Reed; Jack W. Rae; Chris Dyer; Phil Blunsom (NeurIPS, 2018)

A generic framework for privacy preserving deep learning. - Théo Ryffel; Andrew Trask; Morten Dahl; Bobby Wagner; Jason Mancuso; Daniel Rueckert; Jonathan Passerat-Palmbach (CoRR, 2018)

Scaling shared model governance via model splitting. - Miljan Martic; Jan Leike; Andrew Trask; Matteo Hessel; Shane Legg; Pushmeet Kohli (CoRR, 2018)

Sample Efficient Adaptive Text-to-Speech. - Yutian Chen 001; Yannis M. Assael; Brendan Shillingford; David Budden; Scott E. Reed; Heiga Zen; Quan Wang; Luis C. Cobo; Andrew Trask; Ben Laurie; Çaglar Gülçehre; Aäron van den Oord; et al. (ICLR (Poster), 2019)

Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy. - Tom Farrand; Fatemehsadat Mireshghallah; Sahib Singh; Andrew Trask (PPMLP@CCS, 2020)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

Privacy-preserving medical image analysis. - Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Da Lima Costa Junior; Jason Mancuso; Marcus R. Makowski; Daniel Rueckert; Rickmer Braren; Georgios Kaissis (CoRR, 2020)

Beyond Privacy Trade-offs with Structured Transparency. - Andrew Trask; Emma Bluemke; Ben Garfinkel; Claudia Ghezzou Cuervas-Mons; Allan Dafoe (CoRR, 2020)

The future of digital health with federated learning. - Nicola Rieke; Jonny Hancox; Wenqi Li 001; Fausto Milletarì; Holger R. Roth; Shadi Albarqouni; Spyridon Bakas; Mathieu N. Galtier; Bennett A. Landman; Klaus H. Maier-Hein; Sébastien Ourselin; Micah J. Sheller; et al. (npj Digit. Medicine, 2020)

Syft 0.5: A Platform for Universally Deployable Structured Transparency. - Adam James Hall; Madhava Jay; Tudor Cebere; Bogdan Cebere; Koen Lennart van der Veen; George Muraru; Tongye Xu; Patrick Cason; William Abramson; Ayoub Benaissa; Chinmay Shah; Alan Aboudib; et al. (CoRR, 2021)

DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy? - Archit Uniyal; Rakshit Naidu; Sasikanth Kotti; Sahib Singh; Patrik Joslin Kenfack; Fatemehsadat Mireshghallah; Andrew Trask (CoRR, 2021)

Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. - Alexander Ziller; Dmitrii Usynin; Moritz Knolle; Kritika Prakash; Andrew Trask; Rickmer Braren; Marcus R. Makowski; Daniel Rueckert; Georgios Kaissis (CoRR, 2021)

Towards General-purpose Infrastructure for Protecting Scientific Data Under Study. - Andrew Trask; Kritika Prakash (CoRR, 2021)

End-to-end privacy preserving deep learning on multi-institutional medical imaging. - Georgios Kaissis; Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Lima; Jason Mancuso; Friederike Jungmann; Marc-Matthias Steinborn; Andreas Saleh; Marcus R. Makowski; et al. (Nat. Mach. Intell., 2021)

UN Handbook on Privacy-Preserving Computation Techniques. - David W. Archer; Borja de Balle Pigem; Dan Bogdanov; Mark Craddock; Adrià Gascón; Ronald Jansen; Matjaz Jug; Kim Laine; Robert McLellan; Olga Ohrimenko; Mariana Raykova 001; Andrew Trask; et al. (CoRR, 2023)

Exploring the Relevance of Data Privacy-Enhancing Technologies for AI Governance Use Cases. - Emma Bluemke; Tantum Collins; Ben Garfinkel; Andrew Trask (CoRR, 2023)

The Ethics of Advanced AI Assistants. - Iason Gabriel; Arianna Manzini; Geoff Keeling; Lisa Anne Hendricks; Verena Rieser; Hasan Iqbal; Nenad Tomasev; Ira Ktena; Zachary Kenton; Mikel Rodriguez; Seliem El-Sayed; Sasha Brown; et al. (CoRR, 2024)

Open Problems in Technical AI Governance. - Anka Reuel; Ben Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (CoRR, 2024)

Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online. - Steven Adler; Zoë Hitzig; Shrey Jain; Catherine Brewer; Wayne Chang; Renee DiResta; Eddy Lazzarin; Sean McGregor; Wendy Seltzer; Divya Siddarth; Nouran Soliman; Tobin South; et al. (CoRR, 2024)

Open Problems in Technical AI Governance. - Anka Reuel; Benjamin Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (Trans. Mach. Learn. Res., 2025)

Beyond Release: Access Considerations for Generative AI Systems. - Irene Solaiman; Rishi Bommasani; Dan Hendrycks; Ariel Herbert-Voss; Yacine Jernite; Aviya Skowron; Andrew Trask (CoRR, 2025)