Lawrence Chan

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 18

Top Topics

Multi Armed Bandit

Top Venues

Publications

Jason Gross, Rajashree Agrawal, Thomas Kwa, Euan Ong, Chun Hei Yip, Alex Gibson, Soufiane Noubir, Lawrence Chan
Compact Proofs of Model Performance via Mechanistic Interpretability. CoRR (2024)
Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean
Language Models Are Better Than Humans at Next-token Prediction. Trans. Mach. Learn. Res. 2024 (2024)
Richard Ngo, Lawrence Chan, Sören Mindermann
The Alignment Problem from a Deep Learning Perspective. ICLR (2024)
Megan Kinniment, Lucas Jun Koba Sato, Haoxing Du, Brian Goodrich, Max Hasin, Lawrence Chan, Luke Harold Miles, Tao R. Lin, Hjalmar Wijk, Joel Burget, Aaron Ho, Elizabeth Barnes, Paul Christiano
Evaluating Language-Model Agents on Realistic Autonomous Tasks. CoRR (2023)
Bilal Chughtai, Lawrence Chan, Neel Nanda
A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations. ICML (2023)
Neel Nanda, Lawrence Chan, Tom Lieberum, Jess Smith, Jacob Steinhardt
Progress measures for grokking via mechanistic interpretability. ICLR (2023)
Neel Nanda, Lawrence Chan, Tom Lieberum, Jess Smith, Jacob Steinhardt
Progress measures for grokking via mechanistic interpretability. CoRR (2023)
Bilal Chughtai, Lawrence Chan, Neel Nanda
A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations. CoRR (2023)
Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas
Adversarial training for high-stakes reliability. NeurIPS (2022)
Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas
Adversarial Training for High-Stakes Reliability. CoRR (2022)
Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean
Language models are better than humans at next-token prediction. CoRR (2022)
Lawrence Chan, Andrew Critch, Anca D. Dragan
Human irrationality: both bad and good for reward inference. CoRR (2021)
Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan
Optimal Cost Design for Model Predictive Control. L4DC (2021)
Huiling Shao, Lawrence Chan, Fiona Chen, Qilin Ma, Zhiyu Shao, Heng Du
A Fast-Processing Pipeline for Three-dimensional Visualization of Acute Ischemic Stroke lesion topography. BIBM (2021)
Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan
Optimal Cost Design for Model Predictive Control. CoRR (2021)
Harry Giles, Lawrence Chan
Accounting for Human Learning when Inferring Human Preferences. CoRR (2020)
Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan
The Assistive Multi-Armed Bandit. CoRR (2019)
Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan
The Assistive Multi-Armed Bandit. HRI (2019)
Meyrick Chow, Lawrence Chan
Clinical Decision Support using Traditional Chinese Medicine (TCM) Ontology and Text Similarity. Nursing Informatics (2012)
Meyrick Chow, Lawrence Chan
Development and evaluation of a compartmental picture archiving and communications system model for integration and visualization of multidisciplinary biomedical data to facilitate student learning in an integrative health clinic. Comput. Educ. 54 (3) (2010)
Brent J. Liu, Zheng Zhou, Marco A. Gutierrez, Jorge Documet, Lawrence Chan, H. K. Huang
International Internet2 connectivity and performance in medical imaging applications: Bridging the Americas to Asia. J. High Speed Networks 16 (1) (2007)
Zheng Zhou, Marco A. Gutierrez, Jorge Documet, Lawrence Chan, H. K. Huang, Brent J. Liu
The role of a Data Grid in worldwide imaging-based clinical trials. J. High Speed Networks 16 (1) (2007)