עקוב אחר
Jake C. Snell
Jake C. Snell
Postdoctoral Researcher, Princeton University
כתובת אימייל מאומתת בדומיין princeton.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Prototypical networks for few-shot learning‏
J Snell, K Swersky, RS Zemel‏
Advances in Neural Information Processing Systems 30, 4077-4087, 2017‏
98712017
Meta-learning for semi-supervised few-shot classification‏
M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ...‏
International Conference on Learning Representations, 2018‏
16852018
Learning to generate images with perceptual similarity metrics‏
J Snell, K Ridgeway, R Liao, BD Roads, MC Mozer, RS Zemel‏
2017 IEEE International Conference on Image Processing (ICIP), 4277-4281, 2017‏
2222017
Learning latent subspaces in variational autoencoders‏
J Klys, J Snell, R Zemel‏
Advances in Neural Information Processing Systems 31, 6444-6454, 2018‏
1682018
Lorentzian distance learning for hyperbolic representations‏
M Law, R Liao, J Snell, R Zemel‏
International Conference on Machine Learning, 3672-3681, 2019‏
1162019
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes‏
J Snell, R Zemel‏
Ninth International Conference on Learning Representations (ICLR 2021), 2021‏
722021
Dimensionality reduction for representing the knowledge of probabilistic models‏
MT Law, J Snell, A Farahmand, R Urtasun, RS Zemel‏
International Conference on Learning Representations, 2018‏
152018
Few-Shot Attribute Learning‏
M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ...‏
13*2020
Quantile risk control: A flexible framework for bounding the probability of high-loss predictions‏
JC Snell, TP Zollo, Z Deng, T Pitassi, R Zemel‏
arXiv preprint arXiv:2212.13629, 2022‏
72022
Prompt risk control: A rigorous framework for responsible deployment of large language models‏
TP Zollo, T Morrill, Z Deng, JC Snell, T Pitassi, R Zemel‏
arXiv preprint arXiv:2311.13628, 2023‏
62023
Distribution-free statistical dispersion control for societal applications‏
Z Deng, T Zollo, J Snell, T Pitassi, R Zemel‏
Advances in Neural Information Processing Systems 36, 2024‏
42024
Stochastic Segmentation Trees for Multiple Ground Truths.‏
J Snell, RS Zemel‏
UAI, 2017‏
32017
Implicit maximum a posteriori filtering via adaptive optimization‏
GM Bencomo, JC Snell, TL Griffiths‏
arXiv preprint arXiv:2311.10580, 2023‏
22023
Im-promptu: in-context composition from image prompts‏
B Dedhia, M Chang, J Snell, T Griffiths, N Jha‏
Advances in Neural Information Processing Systems 36, 2024‏
12024
A Metalearned Neural Circuit for Nonparametric Bayesian Inference‏
JC Snell, G Bencomo, TL Griffiths‏
arXiv preprint arXiv:2311.14601, 2023‏
12023
Improving Predictor Reliability with Selective Recalibration‏
TP Zollo, Z Deng, JC Snell, T Pitassi, R Zemel‏
arXiv preprint arXiv:2410.05407, 2024‏
2024
Using Contrastive Learning with Generative Similarity to Learn Spaces that Capture Human Inductive Biases‏
R Marjieh, S Kumar, D Campbell, L Zhang, G Bencomo, J Snell, ...‏
arXiv preprint arXiv:2405.19420, 2024‏
2024
Learning to Build Probabilistic Models with Limited Data‏
JC Snell‏
University of Toronto (Canada), 2021‏
2021
Early Exiting in Deep Neural Networks via Dirichlet-based Uncertainty Quantification‏
F Xia, J Snell, TL Griffiths‏
NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles …, 0‏
Binary climate data heightens perceived impact of climate change‏
G Liu, JC Snell, TL Griffiths, R Dubey‏
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מאמרים 1–20