research
∙
06/21/2023
Structure-Aware DropEdge Towards Deep Graph Convolutional Networks
It has been discovered that Graph Convolutional Networks (GCNs) encounte...
share
research
∙
05/30/2023
Subequivariant Graph Reinforcement Learning in 3D Environments
Learning a shared policy that guides the locomotion of different agents ...
research
∙
03/25/2023
Compacting Binary Neural Networks by Sparse Kernel Selection
Binary Neural Network (BNN) represents convolution weights with 1-bit va...
research
∙
10/15/2022
When to Update Your Model: Constrained Model-based Reinforcement Learning
Designing and analyzing model-based RL (MBRL) algorithms with guaranteed...
research
∙
10/14/2022
Learning Active Camera for Multi-Object Navigation
Getting robots to navigate to multiple objects autonomously is essential...
research
∙
10/11/2022
Benefits of Permutation-Equivariance in Auction Mechanisms
Designing an incentive-compatible auction mechanism that maximizes the a...
research
∙
10/11/2022
Planning Assembly Sequence with Graph Transformer
Assembly sequence planning (ASP) is the essential process for modern man...
research
∙
10/04/2022
Bridged Transformer for Vision and Point Cloud 3D Object Detection
3D object detection is a crucial research topic in computer vision, whic...
research
∙
06/23/2022
Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training
Graph instance contrastive learning has been proved as an effective task...
research
∙
06/03/2022
SNAKE: Shape-aware Neural 3D Keypoint Field
Detecting 3D keypoints from point clouds is important for shape reconstr...
research
∙
04/19/2022
Multimodal Token Fusion for Vision Transformers
Many adaptations of transformers have emerged to address the single-moda...
research
∙
03/15/2022
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
After the great success of Vision Transformer variants (ViTs) in compute...
research
∙
03/12/2022
Equivariant Graph Mechanics Networks with Constraints
Learning to reason about relations and dynamics over multiple interactin...
research
∙
02/22/2022
Sound Adversarial Audio-Visual Navigation
Audio-visual navigation task requires an agent to find a sound source in...
research
∙
02/22/2022
Equivariant Graph Hierarchy-Based Neural Networks
Equivariant Graph neural Networks (EGNs) are powerful in characterizing ...
research
∙
02/17/2022
Transformer for Graphs: An Overview from Architecture Perspective
Recently, Transformer model, which has achieved great success in many ar...
research
∙
02/15/2022
Geometrically Equivariant Graph Neural Networks: A Survey
Many scientific problems require to process data in the form of geometri...
research
∙
02/01/2022
Sim2Real Object-Centric Keypoint Detection and Description
Keypoint detection and description play a central role in computer visio...
research
∙
12/04/2021
Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction
Multimodal fusion and multitask learning are two vital topics in machine...
research
∙
12/01/2021
Graph Convolutional Module for Temporal Action Localization in Videos
Temporal action localization has long been researched in computer vision...
research
∙
08/11/2021
Elastic Tactile Simulation Towards Tactile-Visual Perception
Tactile sensing plays an important role in robotic perception and manipu...
research
∙
06/14/2021
PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels
Semi-supervised node classification, as a fundamental problem in graph l...
research
∙
06/10/2021
Adversarial Option-Aware Hierarchical Imitation Learning
It has been a challenge to learning skills for an agent from long-horizo...
research
∙
05/26/2021
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge
With the success of the graph embedding model in both academic and indus...
research
∙
11/23/2020
Elastic Interaction of Particles for Robotic Tactile Simulation
Tactile sensing plays an important role in robotic perception and manipu...
research
∙
11/10/2020
Deep Multimodal Fusion by Channel Exchanging
Deep multimodal fusion by using multiple sources of data for classificat...
research
∙
08/22/2020
Tackling Over-Smoothing for General Graph Convolutional Networks
Increasing the depth of Graph Convolutional Networks (GCN), which in pri...
research
∙
07/12/2020
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Graph Identification (GI) has long been researched in graph learning and...
research
∙
04/07/2020
Dense Regression Network for Video Grounding
We address the problem of video grounding from natural language queries....
research
∙
03/16/2020
Spectral Graph Attention Network
Variants of Graph Neural Networks (GNNs) for representation learning hav...
research
∙
02/29/2020
Reusing Discriminators for Encoding Towards Unsupervised Image-to-Image Translation
Unsupervised image-to-image translation is a central task in computer vi...
research
∙
02/04/2020
Graph Representation Learning via Graphical Mutual Information Maximization
The richness in the content of various information networks such as soci...
research
∙
01/17/2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Social media has been developing rapidly in public due to its nature of ...
research
∙
11/16/2019
Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance
In this paper, we study Reinforcement Learning from Demonstrations (RLfD...
research
∙
10/10/2019
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
This paper studies Learning from Observations (LfO) for imitation learni...
research
∙
09/07/2019
Graph Convolutional Networks for Temporal Action Localization
Most state-of-the-art action localization systems process each action pr...
research
∙
08/18/2019
A Fast and Accurate One-Stage Approach to Visual Grounding
We propose a simple, fast, and accurate one-stage approach to visual gro...
research
∙
08/04/2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models
With the great success of graph embedding model on both academic and ind...
research
∙
08/04/2019
The General Black-box Attack Method for Graph Neural Networks
With the great success of Graph Neural Networks (GNNs) towards represent...
research
∙
07/25/2019
DropEdge: Towards the Very Deep Graph Convolutional Networks for Node Classification
Existing Graph Convolutional Networks (GCNs) are shallow---the number of...
research
∙
07/25/2019
The Truly Deep Graph Convolutional Networks for Node Classification
Existing Graph Convolutional Networks (GCNs) are shallow---the number of...
research
∙
07/10/2019
Label Aware Graph Convolutional Network -- Not All Edges Deserve Your Attention
Graph classification is practically important in many domains. To solve ...
research
∙
07/01/2019
Unsupervised Adversarial Graph Alignment with Graph Embedding
Graph alignment, also known as network alignment, is a fundamental task ...
research
∙
06/27/2019
Adversarial Representation Learning on Large-Scale Bipartite Graphs
Graph representation on large-scale bipartite graphs is central for a va...
research
∙
04/24/2019
Neural Collaborative Subspace Clustering
We introduce the Neural Collaborative Subspace Clustering, a neural mode...
research
∙
04/10/2019
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Node classification and graph classification are two graph learning prob...
research
∙
12/10/2018
Weakly Supervised Dense Event Captioning in Videos
Dense event captioning aims to detect and describe all events of interes...
research
∙
11/21/2018
Progressive Feature Alignment for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) transfers knowledge from a label-ri...
research
∙
09/14/2018
Adaptive Sampling Towards Fast Graph Representation Learning
Graph Convolutional Networks (GCNs) have become a crucial tool on learni...
research
∙
08/24/2018