Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Aaron C. Courville; Chris Pal (CoRR, 2016)

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering. - Tegan Maharaj; Nicolas Ballas; Aaron C. Courville; Christopher Joseph Pal (CoRR, 2016)

Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets. - Evan Racah; Christopher Beckham; Tegan Maharaj; Prabhat; Christopher J. Pal (CoRR, 2016)

Surprisal-Driven Zoneout. - Kamil Rocki; Tomasz Kornuta; Tegan Maharaj (CoRR, 2016)

A Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank Question-Answering. - Tegan Maharaj; Nicolas Ballas; Anna Rohrbach; Aaron C. Courville; Christopher Joseph Pal (CVPR, 2017)

Deep Nets Don't Learn via Memorization. - David Krueger 001; Nicolas Ballas; Stanislaw Jastrzebski; Devansh Arpit; Maxinder S. Kanwal; Tegan Maharaj; Emmanuel Bengio; Asja Fischer; Aaron C. Courville (ICLR (Workshop), 2017)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Aaron C. Courville; Christopher J. Pal (ICLR (Poster), 2017)

A Closer Look at Memorization in Deep Networks. - Devansh Arpit; Stanislaw Jastrzebski; Nicolas Ballas; David Krueger 001; Emmanuel Bengio; Maxinder S. Kanwal; Tegan Maharaj; Asja Fischer; Aaron C. Courville; Yoshua Bengio; Simon Lacoste-Julien (ICML, 2017)

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. - Evan Racah; Christopher Beckham; Tegan Maharaj; Samira Ebrahimi Kahou; Prabhat; Chris Pal (NIPS, 2017)

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)

COVI White Paper. - Hannah Alsdurf; Yoshua Bengio; Tristan Deleu; Prateek Gupta; Daphne Ippolito; Richard Janda; Max Jarvie; Tyler Kolody; Sekoul Krastev; Tegan Maharaj; Robert Obryk; Dan Pilat; et al. (CoRR, 2020)

Hidden Incentives for Auto-Induced Distributional Shift. - David Krueger 001; Tegan Maharaj; Jan Leike (CoRR, 2020)

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. - Prateek Gupta; Tegan Maharaj; Martin Weiss; Nasim Rahaman; Hannah Alsdurf; Abhinav Sharma; Nanor Minoyan; Soren Harnois-Leblanc; Victor Schmidt; Pierre-Luc St-Charles; Tristan Deleu; Andrew Williams; et al. (CoRR, 2020)

Predicting Infectiousness for Proactive Contact Tracing. - Yoshua Bengio; Prateek Gupta; Tegan Maharaj; Nasim Rahaman; Martin Weiss; Tristan Deleu; Eilif Benjamin Müller; Meng Qu; Victor Schmidt; Pierre-Luc St-Charles; Hannah Alsdurf; Olexa Bilaniuk; et al. (ICLR, 2021)

Filling gaps in trustworthy development of AI. - Shahar Avin; Haydn Belfield; Miles Brundage; Gretchen Krueger; Jasmine Wang; Adrian Weller; Markus Anderljung; Igor Krawczuk; David Krueger 001; Jonathan Lebensold; Tegan Maharaj; Noa Zilberman (CoRR, 2021)

Generalizing in the Real World with Representation Learning. - Tegan Maharaj (CoRR, 2022)

Harms from Increasingly Agentic Algorithmic Systems. - Alan Chan; Rebecca Salganik; Alva Markelius; Chris Pang; Nitarshan Rajkumar; Dmitrii Krasheninnikov; Lauro Langosco; Zhonghao He; Yawen Duan; Micah Carroll; Michelle P. Lin; Alex Mayhew; et al. (FAccT, 2023)

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics. - Shoaib Ahmed Siddiqui; Nitarshan Rajkumar; Tegan Maharaj; David Krueger 001; Sara Hooker (ICLR, 2023)

Managing AI Risks in an Era of Rapid Progress. - Yoshua Bengio; Geoffrey E. Hinton; Andrew Yao; Dawn Song; Pieter Abbeel; Yuval Noah Harari; Ya-Qin Zhang; Lan Xue; Shai Shalev-Shwartz; Gillian K. Hadfield; Jeff Clune; Tegan Maharaj; et al. (CoRR, 2023)

Tackling Climate Change with Machine Learning. - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Sasha Luccioni; Tegan Maharaj; et al. (ACM Comput. Surv., 2023)

Machine learning data practices through a data curation lens: An evaluation framework. - Eshta Bhardwaj; Harshit Gujral; Siyi Wu; Ciara Zogheib; Tegan Maharaj; Christoph Becker 001 (FAccT, 2024)

Beyond Predictive Algorithms in Child Welfare. - Erina Seh-Young Moon; Devansh Saxena; Tegan Maharaj; Shion Guha (Graphics Interface, 2024)

Implicit meta-learning may lead language models to trust more reliable sources. - Dmitrii Krasheninnikov; Egor Krasheninnikov; Bruno Kacper Mlodozeniec; Tegan Maharaj; David Krueger 001 (ICML, 2024)

Methods, Applications, and Directions of Learning-to-Rank in NLP Research. - Justin Lee; Gabriel Bernier-Colborne; Tegan Maharaj; Sowmya Vajjala (NAACL-HLT (Findings), 2024)

The State of Data Curation at NeurIPS: An Assessment of Dataset Development Practices in the Datasets and Benchmarks Track. - Eshta Bhardwaj; Harshit Gujral; Siyi Wu; Ciara Zogheib; Tegan Maharaj; Christoph Becker 001 (NeurIPS, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (CoRR, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models. - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (Trans. Mach. Learn. Res., 2024)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)