Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Bronstein, Alex M."'
Autor:
Pegoraro, Marco, Vedula, Sanketh, Rosenberg, Aviv A., Tallini, Irene, Rodolà, Emanuele, Bronstein, Alex M.
Quantile regression (QR) is a statistical tool for distribution-free estimation of conditional quantiles of a target variable given explanatory features. QR is limited by the assumption that the target distribution is univariate and defined on an Euc
Externí odkaz:
http://arxiv.org/abs/2307.01037
Autor:
Rozenberg, Eyal, Karnieli, Aviv, Yesharim, Ofir, Foley-Comer, Joshua, Trajtenberg-Mills, Sivan, Mishra, Sarika, Prabhakar, Shashi, Pratap, Ravindra, Freedman, Daniel, Bronstein, Alex M., Arie, Ady
We propose a novel, physically-constrained and differentiable approach for the generation of D-dimensional qudit states via spontaneous parametric down-conversion (SPDC) in quantum optics. We circumvent any limitations imposed by the inherently stoch
Externí odkaz:
http://arxiv.org/abs/2304.06810
We study the problem of real-time scheduling in a multi-hop millimeter-wave (mmWave) mesh. We develop a model-free deep reinforcement learning algorithm called Adaptive Activator RL (AARL), which determines the subset of mmWave links that should be a
Externí odkaz:
http://arxiv.org/abs/2210.01423
Autor:
Navon, Dan, Bronstein, Alex M.
Vision-Transformers are widely used in various vision tasks. Meanwhile, there is another line of works starting with the MLP-mixer trying to achieve similar performance using mlp-based architectures. Interestingly, until now those mlp-based architect
Externí odkaz:
http://arxiv.org/abs/2208.08191
Autor:
Navon, Dan, Bronstein, Alex M.
Hyperparameter tuning is a common technique for improving the performance of neural networks. Most techniques for hyperparameter search involve an iterated process where the model is retrained at every iteration. However, the expected accuracy improv
Externí odkaz:
http://arxiv.org/abs/2208.08170
Deep neural networks are known to be susceptible to adversarial perturbations -- small perturbations that alter the output of the network and exist under strict norm limitations. While such perturbations are usually discussed as tailored to a specifi
Externí odkaz:
http://arxiv.org/abs/2207.05729
Publikováno v:
The Eleventh International Conference on Learning Representations (ICLR 2023)
Quantile regression (QR) is a powerful tool for estimating one or more conditional quantiles of a target variable $\mathrm{Y}$ given explanatory features $\boldsymbol{\mathrm{X}}$. A limitation of QR is that it is only defined for scalar target varia
Externí odkaz:
http://arxiv.org/abs/2205.14977
A central challenge in building robotic prostheses is the creation of a sensor-based system able to read physiological signals from the lower limb and instruct a robotic hand to perform various tasks. Existing systems typically perform discrete gestu
Externí odkaz:
http://arxiv.org/abs/2202.05204
Autor:
Rozenberg, Eyal, Karnieli, Aviv, Yesharim, Ofir, Foley-Comer, Joshua, Trajtenberg-Mills, Sivan, Freedman, Daniel, Bronstein, Alex M., Arie, Ady
Spontaneous parametric down-conversion in quantum optics is an invaluable resource for the realization of high-dimensional qudits with spatial modes of light. One of the main open challenges is how to directly generate a desirable qudit state in the
Externí odkaz:
http://arxiv.org/abs/2112.05934
Delta-GAN-Encoder: Encoding Semantic Changes for Explicit Image Editing, using Few Synthetic Samples
Understating and controlling generative models' latent space is a complex task. In this paper, we propose a novel method for learning to control any desired attribute in a pre-trained GAN's latent space, for the purpose of editing synthesized and rea
Externí odkaz:
http://arxiv.org/abs/2111.08419