Jake Snell

According to our database1, Jake Snell authored at least 20 papers between 2015 and 2024.

Collaborative distances:

Timeline

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2021
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2023
2024
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Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
ParaVerse: co-design of a parachute rehearsal and training virtual-reality enhanced simulator for the Australian Defence Force: combining a generative co-design framework and an agile approach to development.
Virtual Real., December, 2024

Improving Predictor Reliability with Selective Recalibration.
CoRR, 2024

Using Contrastive Learning with Generative Similarity to Learn Spaces that Capture Human Inductive Biases.
CoRR, 2024

A Metalearned Neural Circuit for Nonparametric Bayesian Inference.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Implicit Maximum a Posteriori Filtering via Adaptive Optimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Distribution-Free Statistical Dispersion Control for Societal Applications.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Im-Promptu: In-Context Composition from Image Prompts.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021
Learning to Build Probabilistic Models with Limited Data.
PhD thesis, 2021

Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Flexible Few-Shot Learning with Contextual Similarity.
CoRR, 2020

2019
Lorentzian Distance Learning for Hyperbolic Representations.
Proceedings of the 36th International Conference on Machine Learning, 2019

Dimensionality Reduction for Representing the Knowledge of Probabilistic Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Learning Latent Subspaces in Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Meta-Learning for Semi-Supervised Few-Shot Classification.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Stochastic Segmentation Trees for Multiple Ground Truths.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Prototypical Networks for Few-shot Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning to generate images with perceptual similarity metrics.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2015
Learning to generate images with perceptual similarity metrics.
CoRR, 2015


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