Search Results for author: Uriel Singer

Found 16 papers, 9 papers with code

Node Embedding over Temporal Graphs

1 code implementation21 Mar 2019 Uriel Singer, Ido Guy, Kira Radinsky

In this work, we present a method for node embedding in temporal graphs.

Clustering Link Prediction +1

Topo2vec: Topography Embedding Using the Fractal Effect

1 code implementation19 Aug 2021 Jonathan Kavitzky, Jonathan Zarecki, Idan Brusilovsky, Uriel Singer

We perform an extensive analysis on several classification tasks and emphasize its effectiveness in detecting the same class on different scales.

Self-Supervised Learning

EqGNN: Equalized Node Opportunity in Graphs

1 code implementation19 Aug 2021 Uriel Singer, Kira Radinsky

To the best of our knowledge, we are the first to optimize GNNs for the equalized odds criteria.

Attribute Fairness

Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce

1 code implementation18 Oct 2021 Uriel Singer, Haggai Roitman, Yotam Eshel, Alexander Nus, Ido Guy, Or Levi, Idan Hasson, Eliyahu Kiperwasser

In e-commerce, the watchlist enables users to track items over time and has emerged as a primary feature, playing an important role in users' shopping journey.

Attribute Sequential Recommendation

tBDFS: Temporal Graph Neural Network Leveraging DFS

1 code implementation12 Jun 2022 Uriel Singer, Haggai Roitman, Ido Guy, Kira Radinsky

A common approach employed by most previous works is to apply a layer that aggregates information from the historical neighbors of a node.

Link Prediction

Learning to Diversify for Product Question Generation

no code implementations6 Jul 2022 Haggai Roitman, Uriel Singer, Yotam Eshel, Alexander Nus, Eliyahu Kiperwasser

For a given product description, our goal is to generate questions that reflect potential user information needs that are either missing or not well covered in the description.

Question Generation Question-Generation

Make-A-Video: Text-to-Video Generation without Text-Video Data

2 code implementations29 Sep 2022 Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, Yaniv Taigman

We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V).

Ranked #3 on Text-to-Video Generation on MSR-VTT (CLIP-FID metric)

Image Generation Super-Resolution +2

AudioGen: Textually Guided Audio Generation

1 code implementation30 Sep 2022 Felix Kreuk, Gabriel Synnaeve, Adam Polyak, Uriel Singer, Alexandre Défossez, Jade Copet, Devi Parikh, Yaniv Taigman, Yossi Adi

Finally, we explore the ability of the proposed method to generate audio continuation conditionally and unconditionally.

Audio Generation Descriptive

Text-To-4D Dynamic Scene Generation

no code implementations26 Jan 2023 Uriel Singer, Shelly Sheynin, Adam Polyak, Oron Ashual, Iurii Makarov, Filippos Kokkinos, Naman Goyal, Andrea Vedaldi, Devi Parikh, Justin Johnson, Yaniv Taigman

We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions.

Scene Generation

Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation

1 code implementation NeurIPS 2023 Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy

Using this web app we build Pick-a-Pic, a large, open dataset of text-to-image prompts and real users' preferences over generated images.

Text-to-Image Generation

Emu Edit: Precise Image Editing via Recognition and Generation Tasks

no code implementations16 Nov 2023 Shelly Sheynin, Adam Polyak, Uriel Singer, Yuval Kirstain, Amit Zohar, Oron Ashual, Devi Parikh, Yaniv Taigman

Lastly, to facilitate a more rigorous and informed assessment of instructable image editing models, we release a new challenging and versatile benchmark that includes seven different image editing tasks.

Image Inpainting Multi-Task Learning +1

D-Flow: Differentiating through Flows for Controlled Generation

no code implementations21 Feb 2024 Heli Ben-Hamu, Omri Puny, Itai Gat, Brian Karrer, Uriel Singer, Yaron Lipman

Taming the generation outcome of state of the art Diffusion and Flow-Matching (FM) models without having to re-train a task-specific model unlocks a powerful tool for solving inverse problems, conditional generation, and controlled generation in general.

Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models

no code implementations2 Mar 2024 Neta Shaul, Uriel Singer, Ricky T. Q. Chen, Matthew Le, Ali Thabet, Albert Pumarola, Yaron Lipman

This paper introduces Bespoke Non-Stationary (BNS) Solvers, a solver distillation approach to improve sample efficiency of Diffusion and Flow models.

Audio Generation Conditional Image Generation +1

Video Editing via Factorized Diffusion Distillation

no code implementations14 Mar 2024 Uriel Singer, Amit Zohar, Yuval Kirstain, Shelly Sheynin, Adam Polyak, Devi Parikh, Yaniv Taigman

We introduce Emu Video Edit (EVE), a model that establishes a new state-of-the art in video editing without relying on any supervised video editing data.

Video Editing Video Generation

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