| 2024 | ICLR | Implicit Maximum a Posteriori Filtering via Adaptive Optimization. | Gianluca M. Bencomo, Jake Snell, Thomas L. Griffiths |
| 2024 | ICLR | Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. | Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel |
| 2023 | ICLR | Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. | Jake Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel |
| 2021 | ICLR | Bayesian Few-Shot Classification with One-vs-Each Plya-Gamma Augmented Gaussian Processes. | Jake Snell, Richard S. Zemel |
| 2019 | ICLR | Dimensionality Reduction for Representing the Knowledge of Probabilistic Models. | Marc T. Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S. Zemel |
| 2019 | ICML | Lorentzian Distance Learning for Hyperbolic Representations. | Marc Teva Law, Renjie Liao, Jake Snell, Richard S. Zemel |
| 2018 | ICLR | Meta-Learning for Semi-Supervised Few-Shot Classification. | Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel |
| 2017 | ICIP | Learning to generate images with perceptual similarity metrics. | Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel |
| 2017 | UAI | Stochastic Segmentation Trees for Multiple Ground Truths. | Jake Snell, Richard S. Zemel |