Search Results for author:
Found 18 papers, 12 papers with code
GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning
Our approach allows for the integration of information at both the individual amino acid level and the entire protein level, enabling a comprehensive and effective learning process through graph-based learning.
Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly
However, reliable time series sales forecasting for e-commerce is difficult, especially during periods with many anomalies, as can often happen during pandemics, abnormal weather, or sports events.
Video Editing via Factorized Diffusion Distillation
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.
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
This paper introduces Bespoke Non-Stationary (BNS) Solvers, a solver distillation approach to improve sample efficiency of Diffusion and Flow models.
D-Flow: Differentiating through Flows for Controlled Generation
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.
Emu Edit: Precise Image Editing via Recognition and Generation Tasks
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.
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
It is also a general-purpose model that can do both text-to-image and image-to-text generation, allowing us to introduce self-contained contrastive decoding methods that produce high-quality outputs.
Ranked #2 on
Text-to-Image Generation
on MS COCO
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
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-4D Dynamic Scene Generation
We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions.
AudioGen: Textually Guided Audio Generation
Finally, we explore the ability of the proposed method to generate audio continuation conditionally and unconditionally.
Ranked #13 on
Audio Generation
on AudioCaps
Make-A-Video: Text-to-Video Generation without Text-Video Data
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)
tBDFS: Temporal Graph Neural Network Leveraging DFS
A common approach employed by most previous works is to apply a layer that aggregates information from the historical neighbors of a node.
KNN-Diffusion: Image Generation via Large-Scale Retrieval
Recent text-to-image models have achieved impressive results.
Ranked #34 on
Text-to-Image Generation
on MS COCO
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce
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.
Topo2vec: Topography Embedding Using the Fractal Effect
We perform an extensive analysis on several classification tasks and emphasize its effectiveness in detecting the same class on different scales.
EqGNN: Equalized Node Opportunity in Graphs
To the best of our knowledge, we are the first to optimize GNNs for the equalized odds criteria.
Node Embedding over Temporal Graphs
In this work, we present a method for node embedding in temporal graphs.
