Chan, Stephanie C. Y.

9 publications

ICML 2025 Strategy Coopetition Explains the Emergence and Transience of In-Context Learning Aaditya K Singh, Ted Moskovitz, Sara Dragutinović, Felix Hill, Stephanie C.Y. Chan, Andrew M Saxe

NeurIPS 2025 The Emergence of Sparse Attention: Impact of Data Distribution and Benefits of Repetition Nicolas Zucchet, Francesco D'Angelo, Andrew Kyle Lampinen, Stephanie C.Y. Chan

ICML 2024 Genie: Generative Interactive Environments Jake Bruce, Michael D Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Maria Elisabeth Bechtle, Feryal Behbahani, Stephanie C.Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando De Freitas, Satinder Singh, Tim Rocktäschel

TMLR 2024 Learned Feature Representations Are Biased by Complexity, Learning Order, Position, and More Andrew Kyle Lampinen, Stephanie C.Y. Chan, Katherine Hermann

ICMLW 2024 Many-Shot In-Context Learning Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Aleksandra Faust, Hugo Larochelle

ICMLW 2024 Many-Shot In-Context Learning Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle

ICML 2024 What Needs to Go Right for an Induction Head? a Mechanistic Study of In-Context Learning Circuits and Their Formation Aaditya K Singh, Ted Moskovitz, Felix Hill, Stephanie C.Y. Chan, Andrew M Saxe

CoLLAs 2022 Zipfian Environments for Reinforcement Learning Stephanie C.Y. Chan, Andrew Kyle Lampinen, Pierre Harvey Richemond, Felix Hill

ICLR 2020 Measuring the Reliability of Reinforcement Learning Algorithms Stephanie C. Y. Chan, Samuel Fishman, John Canny, Anoop Korattikara, Sergio Guadarrama