Zobrazeno 1 - 10
of 5 122
pro vyhledávání: '"A, Kfir"'
Autor:
Qian, Guocheng, Wang, Kuan-Chieh, Patashnik, Or, Heravi, Negin, Ostashev, Daniil, Tulyakov, Sergey, Cohen-Or, Daniel, Aberman, Kfir
We introduce Omni-ID, a novel facial representation designed specifically for generative tasks. Omni-ID encodes holistic information about an individual's appearance across diverse expressions and poses within a fixed-size representation. It consolid
Externí odkaz:
http://arxiv.org/abs/2412.09694
Face image restoration aims to enhance degraded facial images while addressing challenges such as diverse degradation types, real-time processing demands, and, most crucially, the preservation of identity-specific features. Existing methods often str
Externí odkaz:
http://arxiv.org/abs/2412.06753
Autor:
Avrahami, Omri, Patashnik, Or, Fried, Ohad, Nemchinov, Egor, Aberman, Kfir, Lischinski, Dani, Cohen-Or, Daniel
Diffusion models have revolutionized the field of content synthesis and editing. Recent models have replaced the traditional UNet architecture with the Diffusion Transformer (DiT), and employed flow-matching for improved training and sampling. Howeve
Externí odkaz:
http://arxiv.org/abs/2411.14430
We present a complete mechanistic description of the algorithm learned by a minimal non-linear sparse data autoencoder in the limit of large input dimension. The model, originally presented in arXiv:2209.10652, compresses sparse data vectors through
Externí odkaz:
http://arxiv.org/abs/2410.12101
In this paper, we establish the global convergence of the actor-critic algorithm with a significantly improved sample complexity of $O(\epsilon^{-3})$, advancing beyond the existing local convergence results. Previous works provide local convergence
Externí odkaz:
http://arxiv.org/abs/2410.08868
The 'l-Doubling' phenomenon emanates from the coupling between molecular rotations and perpendicular vibrations (bending modes) in polyatomic molecules. This elusive phenomenon has been largely discarded in laser-induced molecular alignment. Here we
Externí odkaz:
http://arxiv.org/abs/2410.06752
Autor:
Shkolnik, Moran, Fishman, Maxim, Chmiel, Brian, Ben-Yaacov, Hilla, Banner, Ron, Levy, Kfir Yehuda
Quantization has established itself as the primary approach for decreasing the computational and storage expenses associated with Large Language Models (LLMs) inference. The majority of current research emphasizes quantizing weights and activations t
Externí odkaz:
http://arxiv.org/abs/2410.03185
The energy consumption of neural network inference has become a topic of paramount importance with the growing success and adoption of deep neural networks. Analog optical neural networks (ONNs) can reduce the energy of matrix-vector multiplication i
Externí odkaz:
http://arxiv.org/abs/2409.12305
Distributed applications based on micro-services in edge computing are becoming increasingly popular due to the rapid evolution of mobile networks. While Kubernetes is the default framework when it comes to orchestrating and managing micro-service-ba
Externí odkaz:
http://arxiv.org/abs/2409.09278
Autor:
Ordan, Yoad, Bloom, Yuval, Levin, Tamar, Sulimany, Kfir, Hollingsworth, Jennifer A., Rapaport, Ronen
The original proposal of quantum key distribution (QKD) was based on ideal single photon sources, which 40 years later, are still challenging to develop. Therefore, the development of decoy state protocols using weak coherent states (WCS) from lasers
Externí odkaz:
http://arxiv.org/abs/2409.07939