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pro vyhledávání: '"Weill, Jonathan"'
Despite the many advances of Large Language Models (LLMs) and their unprecedented rapid evolution, their impact and integration into every facet of our daily lives is limited due to various reasons. One critical factor hindering their widespread adop
Externí odkaz:
http://arxiv.org/abs/2403.02889
Autor:
Barkan, Oren, Elisha, Yehonatan, Weill, Jonathan, Asher, Yuval, Eshel, Amit, Koenigstein, Noam
This paper presents Deep Integrated Explanations (DIX) - a universal method for explaining vision models. DIX generates explanation maps by integrating information from the intermediate representations of the model, coupled with their corresponding g
Externí odkaz:
http://arxiv.org/abs/2310.15368
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond
Autor:
Barkan, Oren, Reiss, Tal, Weill, Jonathan, Katz, Ori, Hirsch, Roy, Malkiel, Itzik, Koenigstein, Noam
Visual similarities discovery (VSD) is an important task with broad e-commerce applications. Given an image of a certain object, the goal of VSD is to retrieve images of different objects with high perceptual visual similarity. Although being a highl
Externí odkaz:
http://arxiv.org/abs/2308.14753
Autor:
Barkan, Oren, Caciularu, Avi, Rejwan, Idan, Katz, Ori, Weill, Jonathan, Malkiel, Itzik, Koenigstein, Noam
We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is
Externí odkaz:
http://arxiv.org/abs/2306.16326
Autor:
Malkiel, Itzik, Ginzburg, Dvir, Barkan, Oren, Caciularu, Avi, Weill, Jonathan, Koenigstein, Noam
Recently, there has been growing interest in the ability of Transformer-based models to produce meaningful embeddings of text with several applications, such as text similarity. Despite significant progress in the field, the explanations for similari
Externí odkaz:
http://arxiv.org/abs/2208.06612
Publikováno v:
In Cell Reports 22 October 2024 43(10)
A major challenge in collaborative filtering methods is how to produce recommendations for cold items (items with no ratings), or integrate cold item into an existing catalog. Over the years, a variety of hybrid recommendation models have been propos
Externí odkaz:
http://arxiv.org/abs/2112.07615
Autor:
Lin, Zudi, Wei, Donglai, Petkova, Mariela D., Wu, Yuelong, Ahmed, Zergham, K, Krishna Swaroop, Zou, Silin, Wendt, Nils, Boulanger-Weill, Jonathan, Wang, Xueying, Dhanyasi, Nagaraju, Arganda-Carreras, Ignacio, Engert, Florian, Lichtman, Jeff, Pfister, Hanspeter
Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. However, current datasets for neuronal nuclei usually contain volumes smal
Externí odkaz:
http://arxiv.org/abs/2107.05840
Autor:
Odstrcil, Iris, Petkova, Mariela D., Haesemeyer, Martin, Boulanger-Weill, Jonathan, Nikitchenko, Maxim, Gagnon, James A., Oteiza, Pablo, Schalek, Richard, Peleg, Adi, Portugues, Ruben, Lichtman, Jeff W., Engert, Florian
Publikováno v:
In Current Biology 10 January 2022 32(1):176-189
Manifold learning methods are useful for high dimensional data analysis. Many of the existing methods produce a low dimensional representation that attempts to describe the intrinsic geometric structure of the original data. Typically, this process i
Externí odkaz:
http://arxiv.org/abs/1603.02194