research
∙
04/02/2023
Sketch-based Video Object Localization
We introduce Sketch-based Video Object Localization (SVOL), a new task a...
share
research
∙
03/29/2023
Self-positioning Point-based Transformer for Point Cloud Understanding
Transformers have shown superior performance on various computer vision ...
research
∙
12/07/2022
RainUNet for Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts
This paper presents a solution to the Weather4cast 2022 Challenge Stage ...
research
∙
12/02/2022
Relation-aware Language-Graph Transformer for Question Answering
Question Answering (QA) is a task that entails reasoning over natural la...
research
∙
06/29/2022
Deformable Graph Transformer
Transformer-based models have been widely used and achieved state-of-the...
research
∙
04/21/2022
On a conjecture of Talagrand on selector processes and a consequence on positive empirical processes
For appropriate Gaussian processes, Michel Talagrand (1987) proved that ...
research
∙
03/31/2022
A Proof of the Kahn-Kalai Conjecture
We prove the "expectation-threshold" conjecture of Kahn and Kalai....
research
∙
03/26/2022
Metropolis-Hastings Data Augmentation for Graph Neural Networks
Graph Neural Networks (GNNs) often suffer from weak-generalization due t...
research
∙
01/25/2022
Explore and Match: End-to-End Video Grounding with Transformer
We present a new paradigm named explore-and-match for video grounding, w...
research
∙
12/29/2021
Deformable Graph Convolutional Networks
Graph neural networks (GNNs) have significantly improved the representat...
research
∙
11/30/2021
Donut: Document Understanding Transformer without OCR
Understanding document images (e.g., invoices) has been an important res...
research
∙
03/01/2021
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
In recent years, graph neural networks (GNNs) have been widely adopted i...
research
∙
10/24/2020
Deep neural network for solving differential equations motivated by Legendre-Galerkin approximation
Nonlinear differential equations are challenging to solve numerically an...
research
∙
10/20/2020
Robust Neural Networks inspired by Strong Stability Preserving Runge-Kutta methods
Deep neural networks have achieved state-of-the-art performance in a var...
research
∙
07/16/2020
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
Graph neural networks have shown superior performance in a wide range of...
research
∙
10/29/2019