Chris J. Maddison
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
22
Venues
5
Active years
2014–2025
Best venue rank
A*
Where they publish
Papers
22 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. | Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si |
| 2025 | ICLR | MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures. | Anvith Thudi, Chris J. Maddison |
| 2025 | ICML | MixMin: Finding Data Mixtures via Convex Minimization. | Anvith Thudi, Evianne Rovers, Yangjun Ruan, Tristan Thrush, Chris J. Maddison |
| 2024 | COLT | Minimax Linear Regression under the Quantile Risk. | Ayoub El Hanchi, Chris J. Maddison, Murat A. Erdogdu |
| 2024 | ICLR | Identifying the Risks of LM Agents with an LM-Emulated Sandbox. | Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto |
| 2024 | ICML | Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs. | Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison |
| 2023 | ICLR | Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions. | Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison |
| 2022 | ICLR | Optimal Representations for Covariate Shift. | Yangjun Ruan, Yann Dubois, Chris J. Maddison |
| 2022 | ICML | Augment with Care: Contrastive Learning for Combinatorial Problems. | Haonan Duan, Pashootan Vaezipoor, Max B. Paulus, Yangjun Ruan, Chris J. Maddison |
| 2022 | ICML | Stochastic Reweighted Gradient Descent. | Ayoub El Hanchi, David A. Stephens, Chris J. Maddison |
| 2022 | ICML | Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. | Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison |
| 2022 | ICML | Bayesian Nonparametrics for Offline Skill Discovery. | Valentin Villecroze, Harry J. Braviner, Panteha Naderian, Chris J. Maddison, Gabriel Loaiza-Ganem |
| 2021 | AAAI | Learning Branching Heuristics for Propositional Model Counting. | Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus |
| 2021 | ICLR | Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. | Max B. Paulus, Chris J. Maddison, Andreas Krause |
| 2021 | ICML | Oops I Took A Gradient: Scalable Sampling for Discrete Distributions. | Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris J. Maddison |
| 2021 | ICML | Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. | Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison |
| 2019 | ICLR | Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives. | George Tucker, Dieterich Lawson, Shixiang Gu, Chris J. Maddison |
| 2018 | ICML | Tighter Variational Bounds are Not Necessarily Better. | Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh |
| 2017 | ICLR | Particle Value Functions. | Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh |
| 2017 | ICLR | The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables. | Chris J. Maddison, Andriy Mnih, Yee Whye Teh |
| 2017 | ICLR | REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models. | George Tucker, Andriy Mnih, Chris J. Maddison, Jascha Sohl-Dickstein |
| 2014 | ICML | Structured Generative Models of Natural Source Code. | Chris J. Maddison, Daniel Tarlow |