Cikkek nyilvánosan hozzáférhető megbízással - Jake C. SnellTovábbi információ
Valahol hozzáférhető: 8
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
Megbízások: US National Science Foundation
Learning latent subspaces in variational autoencoders
J Klys, J Snell, R Zemel
Advances in Neural Information Processing Systems 31, 6444-6454, 2018
Megbízások: Natural Sciences and Engineering Research Council of Canada
Lorentzian distance learning for hyperbolic representations
M Law, R Liao, J Snell, R Zemel
International Conference on Machine Learning, 3672-3681, 2019
Megbízások: US Office of the Director of National Intelligence
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
Megbízások: US Office of the Director of National Intelligence
Few-Shot Attribute Learning
M Ren, E Triantafillou, KC Wang, J Lucas, J Snell, X Pitkow, AS Tolias, ...
Megbízások: US Office of the Director of National Intelligence, Natural Sciences and …
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, 40342-40366, 2023
Megbízások: US Department of Defense
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, 53261-53274, 2023
Megbízások: US National Science Foundation, US Department of Defense
Stochastic Segmentation Trees for Multiple Ground Truths.
J Snell, RS Zemel
UAI, 2017
Megbízások: Natural Sciences and Engineering Research Council of Canada
A publikációs és a finanszírozási adatokat számítógépes program határozza meg, automatikusan.