Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Fallah, Kion"'
Autor:
Zhang, Chris, Biswas, Sourav, Wong, Kelvin, Fallah, Kion, Zhang, Lunjun, Chen, Dian, Casas, Sergio, Urtasun, Raquel
Large-scale data is crucial for learning realistic and capable driving policies. However, it can be impractical to rely on scaling datasets with real data alone. The majority of driving data is uninteresting, and deliberately collecting new long-tail
Externí odkaz:
http://arxiv.org/abs/2409.18218
Self-supervised learning of deep neural networks has become a prevalent paradigm for learning representations that transfer to a variety of downstream tasks. Similar to proposed models of the ventral stream of biological vision, it is observed that t
Externí odkaz:
http://arxiv.org/abs/2306.13544
Deep generative models have the capacity to render high fidelity images of content like human faces. Recently, there has been substantial progress in conditionally generating images with specific quantitative attributes, like the emotion conveyed by
Externí odkaz:
http://arxiv.org/abs/2304.00185
Autor:
Loeffler, Christoffer, Fallah, Kion, Fenu, Stefano, Zanca, Dario, Eskofier, Bjoern, Rozell, Christopher John, Mutschler, Christopher
Publikováno v:
Transactions on Machine Learning Research 04/2023 https://openreview.net/forum?id=oq3tx5kinu
Humans innately measure distance between instances in an unlabeled dataset using an unknown similarity function. Distance metrics can only serve as proxy for similarity in information retrieval of similar instances. Learning a good similarity functio
Externí odkaz:
http://arxiv.org/abs/2207.12710
Autor:
Fallah, Kion, Rozell, Christopher J.
Sparse coding strategies have been lauded for their parsimonious representations of data that leverage low dimensional structure. However, inference of these codes typically relies on an optimization procedure with poor computational scaling in high-
Externí odkaz:
http://arxiv.org/abs/2205.03665
Isolating and controlling specific features in the outputs of generative models in a user-friendly way is a difficult and open-ended problem. We develop techniques that allow an oracle user to generate an image they are envisioning in their head by a
Externí odkaz:
http://arxiv.org/abs/2204.14189
Many machine learning techniques incorporate identity-preserving transformations into their models to generalize their performance to previously unseen data. These transformations are typically selected from a set of functions that are known to maint
Externí odkaz:
http://arxiv.org/abs/2106.12096
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers