Chris J. Maddison
University of Toronto
H-index: 24
North America-Canada
Top articles of Chris J. Maddison
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs | arXiv preprint arXiv:2402.08733 | Daniel D Johnson Daniel Tarlow David Duvenaud Chris J Maddison | 2024/2/13 |
Identifying the risks of lm agents with an lm-emulated sandbox | arXiv preprint arXiv:2309.15817 | Yangjun Ruan Honghua Dong Andrew Wang Silviu Pitis Yongchao Zhou | 2023/9/25 |
Probabilistic invariant learning with randomized linear classifiers | Advances in Neural Information Processing Systems | Leonardo Cotta Gal Yehuda Assaf Schuster Chris J Maddison | 2023 |
The shaped transformer: Attention models in the infinite depth-and-width limit | Advances in Neural Information Processing Systems | Lorenzo Noci Chuning Li Mufan Li Bobby He Thomas Hofmann | 2024/2/13 |
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions | Daniel D Johnson Ayoub El Hanchi Chris J Maddison | 2023 | |
Benchmarking neural network training algorithms | arXiv preprint arXiv:2306.07179 | George E Dahl Frank Schneider Zachary Nado Naman Agarwal Chandramouli Shama Sastry | 2023/6/12 |
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy | Honghua Dong Jiawei Xu Yu Yang Rui Zhao Shiwen Wu | 2023 | |
Learning to cut by looking ahead: Cutting plane selection via imitation learning | Max B Paulus Giulia Zarpellon Andreas Krause Laurent Charlin Chris Maddison | 2022 | |
Bayesian nonparametrics for offline skill discovery | Valentin Villecroze Harry Braviner Panteha Naderian Chris Maddison Gabriel Loaiza-Ganem | 2022 | |
Optimal Representations for Covariate Shift | In International Conference on Learning Representations (ICLR) 2022 | Yangjun Ruan Yann Dubois Chris J Maddison | 2022/1 |
The machine learning for combinatorial optimization competition (ml4co): Results and insights | Maxime Gasse Simon Bowly Quentin Cappart Jonas Charfreitag Laurent Charlin | 2022/7/20 | |
Stochastic Reweighted Gradient Descent | Ayoub El Hanchi David Stephens Chris Maddison | 2022 | |
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator | ICLR | Max B Paulus Chris J Maddison Andreas Krause | 2021 |
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding | In International Conference on Machine Learning (ICML) 2021 | Yangjun Ruan Karen Ullrich Daniel Severo James Townsend Ashish Khisti | 2021/2/22 |
Learning Branching Heuristics for Propositional Model Counting | Proceedings of the AAAI Conference on Artificial Intelligence | Pashootan Vaezipoor Gil Lederman Yuhuai Wu Chris Maddison Roger B Grosse | 2021/5/18 |
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions | Will Grathwohl Kevin Swersky Milad Hashemi David Duvenaud Chris Maddison | 2021/7/1 | |
Dual space preconditioning for gradient descent | SIAM Journal on Optimization | Chris J Maddison Daniel Paulin Yee Whye Teh Arnaud Doucet | 2021 |
Lossy Compression for Lossless Prediction | NeurIPS | Yann Dubois Benjamin Bloem-Reddy Karen Ullrich Chris J Maddison | 2021/6/21 |
Learning to Extend Program Graphs to Work-in-Progress Code | arXiv preprint arXiv:2105.14038 | Xuechen Li Chris J Maddison Daniel Tarlow | 2021/5/28 |
Learning Generalized Gumbel-max Causal Mechanisms | Advances in Neural Information Processing Systems | Guy Lorberbom Daniel D Johnson Chris J Maddison Daniel Tarlow Tamir Hazan | 2021/12/6 |
Co-Authors
