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09/17/2023
Kinematics-aware Trajectory Generation and Prediction with Latent Stochastic Differential Modeling
Trajectory generation and trajectory prediction are two critical tasks f...
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09/03/2023
Multi-Relational Contrastive Learning for Recommendation
Personalized recommender systems play a crucial role in capturing users'...
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08/23/2023
When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation
Federated learning (FL) enables collaborative model training across dist...
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08/22/2023
How Expressive are Graph Neural Networks in Recommendation?
Graph Neural Networks (GNNs) have demonstrated superior performance on v...
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08/10/2023
SSLRec: A Self-Supervised Learning Library for Recommendation
Self-supervised learning (SSL) has gained significant interest in recent...
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07/31/2023
DAVIS: High-Quality Audio-Visual Separation with Generative Diffusion Models
We propose DAVIS, a Diffusion model-based Audio-VIusal Separation framew...
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07/25/2023
Feature Importance Measurement based on Decision Tree Sampling
Random forest is effective for prediction tasks but the randomness of tr...
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07/06/2023
Knowledge Graph Self-Supervised Rationalization for Recommendation
In this paper, we introduce a new self-supervised rationalization method...
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06/27/2023
FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation
Medical image segmentation of gadolinium enhancement magnetic resonance ...
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06/19/2023
Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation
Spatial-temporal graph learning has emerged as a promising solution for ...
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06/14/2023
SaliencyCut: Augmenting Plausible Anomalies for Open-set Fine-Grained Anomaly Detection
Open-set fine-grained anomaly detection is a challenging task that requi...
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06/14/2023
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting
Traffic forecasting plays a critical role in smart city initiatives and ...
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06/04/2023
Graph Transformer for Recommendation
This paper presents a novel approach to representation learning in recom...
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05/22/2023
Denoised Self-Augmented Learning for Social Recommendation
Social recommendation is gaining increasing attention in various online ...
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05/18/2023
Adaptive Graph Contrastive Learning for Recommendation
Recently, graph neural networks (GNNs) have been successfully applied to...
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05/08/2023
Graph Masked Autoencoder for Sequential Recommendation
While some powerful neural network architectures (e.g., Transformer, Gra...
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05/04/2023
Disentangled Contrastive Collaborative Filtering
Recent studies show that graph neural networks (GNNs) are prevalent to m...
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03/31/2023
POLAR-Express: Efficient and Precise Formal Reachability Analysis of Neural-Network Controlled Systems
Neural networks (NNs) playing the role of controllers have demonstrated ...
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03/27/2023
Modeling Population Movements under Uncertainty at the Border in Humanitarian Crises: A Situational Analysis Tool
Humanitarian agencies must be prepared to mobilize quickly in response t...
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03/23/2023
Egocentric Audio-Visual Object Localization
Humans naturally perceive surrounding scenes by unifying sound and sight...
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03/21/2023
Debiased Contrastive Learning for Sequential Recommendation
Current sequential recommender systems are proposed to tackle the dynami...
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03/15/2023
Graph-less Collaborative Filtering
Graph neural networks (GNNs) have shown the power in representation lear...
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03/14/2023
Disentangled Graph Social Recommendation
Social recommender systems have drawn a lot of attention in many online ...
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03/14/2023
Automated Self-Supervised Learning for Recommendation
Graph neural networks (GNNs) have emerged as the state-of-the-art paradi...
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03/02/2023
Heterogeneous Graph Contrastive Learning for Recommendation
Graph Neural Networks (GNNs) have become powerful tools in modeling grap...
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02/21/2023
Multi-Modal Self-Supervised Learning for Recommendation
The online emergence of multi-modal sharing platforms (eg, TikTok, Youtu...
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02/17/2023
Multi-Behavior Graph Neural Networks for Recommender System
Recommender systems have been demonstrated to be effective to meet user'...
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02/16/2023
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation
Graph neural network (GNN) is a powerful learning approach for graph-bas...
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02/04/2023
AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis
Human perception of the complex world relies on a comprehensive analysis...
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01/30/2023
Do We Really Need Graph Neural Networks for Traffic Forecasting?
Spatio-temporal graph neural networks (STGNN) have become the most popul...
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12/07/2022
Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction
Robust prediction of citywide traffic flows at different time periods pl...
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11/15/2022
Quantifying the Impact of Label Noise on Federated Learning
Federated Learning (FL) is a distributed machine learning paradigm where...
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11/12/2022
Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning
Detecting anomalous trajectories has become an important task in many lo...
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10/01/2022
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning
Even pruned by the state-of-the-art network compression methods, Graph N...
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09/29/2022
Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
It is quite challenging to ensure the safety of reinforcement learning (...
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08/15/2022
A Tool for Neural Network Global Robustness Certification and Training
With the increment of interest in leveraging machine learning technology...
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08/12/2022
Multiplex Heterogeneous Graph Convolutional Network
Heterogeneous graph convolutional networks have gained great popularity ...
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08/05/2022
Localized Sparse Incomplete Multi-view Clustering
Incomplete multi-view clustering, which aims to solve the clustering pro...
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07/28/2022
Self-Supervised Hypergraph Transformer for Recommender Systems
Graph Neural Networks (GNNs) have been shown as promising solutions for ...
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07/12/2022
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Learning dynamic user preference has become an increasingly important co...
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06/26/2022
Cross-Silo Federated Learning: Challenges and Opportunities
Federated learning (FL) is an emerging technology that enables the train...
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06/06/2022
Multi-Behavior Sequential Recommendation with Temporal Graph Transformer
Modeling time-evolving preferences of users with their sequential item i...
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05/24/2022
RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation
Recipe recommendation systems play an essential role in helping people d...
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05/08/2022
Mutual Distillation Learning Network for Trajectory-User Linking
Trajectory-User Linking (TUL), which links trajectories to users who gen...
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05/02/2022
Knowledge Graph Contrastive Learning for Recommendation
Knowledge Graphs (KGs) have been utilized as useful side information to ...
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04/26/2022
Hypergraph Contrastive Collaborative Filtering
Collaborative Filtering (CF) has emerged as fundamental paradigms for pa...
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04/20/2022
Scalable Motif Counting for Large-scale Temporal Graphs
One fundamental problem in temporal graph analysis is to count the occur...
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04/18/2022
Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction
Crime has become a major concern in many cities, which calls for the ris...
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04/15/2022
MetaSets: Meta-Learning on Point Sets for Generalizable Representations
Deep learning techniques for point clouds have achieved strong performan...
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03/26/2022