Artículos con órdenes de acceso público - Thomas HofmannMás información
Disponibles en algún lugar: 13
Hyperbolic neural networks
O Ganea, G Bécigneul, T Hofmann
Advances in neural information processing systems 31, 2018
Órdenes: Swiss National Science Foundation
Hyperbolic entailment cones for learning hierarchical embeddings
O Ganea, G Bécigneul, T Hofmann
International conference on machine learning, 1646-1655, 2018
Órdenes: Swiss National Science Foundation
Fast cosmic web simulations with generative adversarial networks
AC Rodríguez, T Kacprzak, A Lucchi, A Amara, R Sgier, J Fluri, ...
Computational Astrophysics and Cosmology 5 (1), 1-11, 2018
Órdenes: Swiss National Science Foundation
Predicting structured objects with support vector machines
T Joachims, T Hofmann, Y Yue, CN Yu
Communications of the ACM 52 (11), 97-104, 2009
Órdenes: US National Institutes of Health
Cosmological constraints with deep learning from KiDS-450 weak lensing maps
J Fluri, T Kacprzak, A Lucchi, A Refregier, A Amara, T Hofmann, ...
Physical Review D 100 (6), 063514, 2019
Órdenes: Swiss National Science Foundation
Cosmological constraints from noisy convergence maps through deep learning
J Fluri, T Kacprzak, A Refregier, A Amara, A Lucchi, T Hofmann
Physical Review D 98 (12), 123518, 2018
Órdenes: Swiss National Science Foundation
Convolutional generation of textured 3d meshes
D Pavllo, G Spinks, T Hofmann, MF Moens, A Lucchi
Advances in Neural Information Processing Systems 33, 870-882, 2020
Órdenes: Swiss National Science Foundation, Research Foundation (Flanders), European …
Ledeepchef deep reinforcement learning agent for families of text-based games
L Adolphs, T Hofmann
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7342-7349, 2020
Órdenes: Swiss National Science Foundation
Learning generative models of textured 3d meshes from real-world images
D Pavllo, J Kohler, T Hofmann, A Lucchi
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Órdenes: Swiss National Science Foundation
Full analysis of KiDS-1000 weak lensing maps using deep learning
J Fluri, T Kacprzak, A Lucchi, A Schneider, A Refregier, T Hofmann
Physical Review D 105 (8), 083518, 2022
Órdenes: Swiss National Science Foundation, German Research Foundation, Netherlands …
Cosmological N-body simulations: a challenge for scalable generative models
N Perraudin, A Srivastava, A Lucchi, T Kacprzak, T Hofmann, A Réfrégier
Computational Astrophysics and Cosmology 6, 1-17, 2019
Órdenes: Swiss National Science Foundation
Controlling style and semantics in weakly-supervised image generation
D Pavllo, A Lucchi, T Hofmann
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Órdenes: Swiss National Science Foundation, Research Foundation (Flanders)
OpenFilter: a framework to democratize research access to social media AR filters
P Riccio, B Psomas, F Galati, F Escolano, T Hofmann, N Oliver
Advances in Neural Information Processing Systems 35, 12491-12503, 2022
Órdenes: European Commission, Agence Nationale de la Recherche, Gobierno de España
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