Snell, Jake

15 publications

NeurIPSW 2024 Early Exiting in Deep Neural Networks via Dirichlet-Based Uncertainty Quantification Feng Xia, Jake Snell, Thomas L. Griffiths

ICLR 2024 Implicit Maximum a Posteriori Filtering via Adaptive Optimization Gianluca Bencomo, Jake Snell, Thomas L. Griffiths

TMLR 2024 Improving Predictor Reliability with Selective Recalibration Thomas P Zollo, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel

ICLR 2024 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 Zemel

NeurIPS 2023 Distribution-Free Statistical Dispersion Control for Societal Applications Zhun Deng, Thomas Zollo, Jake Snell, Toniann Pitassi, Richard S. Zemel

NeurIPS 2023 Im-Promptu: In-Context Composition from Image Prompts Bhishma Dedhia, Michael Chang, Jake Snell, Tom Griffiths, Niraj Jha

NeurIPSW 2023 Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models Thomas Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel

ICLR 2023 Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions Jake Snell, Thomas P Zollo, Zhun Deng, Toniann Pitassi, Richard Zemel

ICLR 2021 Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake Snell, Richard Zemel

ICLR 2019 Dimensionality Reduction for Representing the Knowledge of Probabilistic Models Marc T Law, Jake Snell, Amir-massoud Farahmand, Raquel Urtasun, Richard S Zemel

ICML 2019 Lorentzian Distance Learning for Hyperbolic Representations Marc Law, Renjie Liao, Jake Snell, Richard Zemel

NeurIPS 2018 Learning Latent Subspaces in Variational Autoencoders Jack Klys, Jake Snell, Richard Zemel

ICLR 2018 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

NeurIPS 2017 Prototypical Networks for Few-Shot Learning Jake Snell, Kevin Swersky, Richard Zemel

UAI 2017 Stochastic Segmentation Trees for Multiple Ground Truths Jake Snell, Richard S. Zemel