Andrew Trask

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 25

Top Topics

Privacy Preserving

Top Venues

Nat. Mach. Intell.

Publications

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, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika
The Ethics of Advanced AI Assistants. CoRR (2024)
Anka Reuel, Ben Bucknall, Stephen Casper, Tim Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Alexandra Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager
Open Problems in Technical AI Governance. CoRR (2024)
Emma Bluemke, Tantum Collins, Ben Garfinkel, Andrew Trask
Exploring the Relevance of Data Privacy-Enhancing Technologies for AI Governance Use Cases. CoRR (2023)
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, Andrew Trask, Simon Wardley
UN Handbook on Privacy-Preserving Computation Techniques. CoRR (2023)
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kritika Prakash, Andrew Trask, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Georgios Kaissis
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation. CoRR (2021)
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, Théo Ryffel, Kritika Prakash, Tom Titcombe, Varun Kumar Khare, Maddie Shang, Ionesio Junior, Animesh Gupta, Jason Paumier, Nahua Kang, Vova Manannikov, Andrew Trask
Syft 0.5: A Platform for Universally Deployable Structured Transparency. CoRR (2021)
Archit Uniyal, Rakshit Naidu, Sasikanth Kotti, Sahib Singh, Patrik Joslin Kenfack, Fatemehsadat Mireshghallah, Andrew Trask
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy? CoRR (2021)
Andrew Trask, Kritika Prakash
Towards General-purpose Infrastructure for Protecting Scientific Data Under Study. CoRR (2021)
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, Daniel Rueckert, Rickmer Braren
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3 (6) (2021)
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy. PPMLP@CCS (2020)
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletarì, Holger R. Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso
The future of digital health with federated learning. npj Digit. Medicine 3 (2020)
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
Privacy-preserving medical image analysis. CoRR (2020)
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, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR (2020)
Andrew Trask, Emma Bluemke, Ben Garfinkel, Claudia Ghezzou Cuervas-Mons, Allan Dafoe
Beyond Privacy Trade-offs with Structured Transparency. CoRR (2020)
Tom Farrand, Fatemehsadat Mireshghallah, Sahib Singh, Andrew Trask
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy. CoRR (2020)
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso
The Future of Digital Health with Federated Learning. CoRR (2020)
Yutian Chen, 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, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. ICLR (Poster) (2019)
Miljan Martic, Jan Leike, Andrew Trask, Matteo Hessel, Shane Legg, Pushmeet Kohli
Scaling shared model governance via model splitting. CoRR (2018)
Yutian Chen, 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, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. CoRR (2018)
Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom
Neural Arithmetic Logic Units. NeurIPS (2018)
Andrew Trask, Felix Hill, Scott E. Reed, Jack W. Rae, Chris Dyer, Phil Blunsom
Neural Arithmetic Logic Units. CoRR (2018)
Théo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, Jonathan Passerat-Palmbach
A generic framework for privacy preserving deep learning. CoRR (2018)
Andrew Trask, David Gilmore, Matthew Russell
Modeling Order in Neural Word Embeddings at Scale. CoRR (2015)
Andrew Trask, David Gilmore, Matthew Russell
Modeling Order in Neural Word Embeddings at Scale. ICML (2015)
Andrew Trask, Phil Michalak, John Liu
sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings. CoRR (2015)