This page is an archive for papers reviewed by members of the Network Science Lab, along with corresponding presentation materials, as part of the NS-CUK Weekly Seminar series. Launched in Fall 2022, this seminar series is intended to be a platform for the members of the Network Science Lab at the Catholic University of Korea to exchange insights and understanding of state-of-the-art AI methodologies and models for graph mining.
Previous Years
2024
Dec 16th, 2024
V.T. Hoang, Review on "Data-Centric Learning from Unlabeled Graphs with Diffusion Model", NeurIPS 2024
T.B.T. Do, Review on "Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images", NeurIPS 2024
J.H. Shim, Review on "Learning and Optimization of Implicit Negative Feedback for Industrial short-video Recommendation System", CIKM 2023
Dec 9th, 2024
V.T. Hoang, Review on "CHEER: Centrality-aware High-order Event Reasoning Network for Document-level Event Causality Identification", ACL 2023
T.B.T. Do, Review on "CYCLO : Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos", NeurIPS 2024
Dec 2nd, 2024
V.T. Hoang, Review on "Multi-View Mixture-of-Experts for Predicting Molecular Properties Using SMILES, SELFIES, and Graph-Based Representations", NeurIPS 2024
T.B.T. Do, Review on "Long-range Brain Graph Transformer", NeurIPS 2024
J.H. Shim, Review on "Denoising Implicit Feedback for Recommendation", WSDM 2021
Nov 25th, 2024
V.T. Hoang, Review on "Few-Shot Graph Learning for Molecular Property Prediction", WWW 2021
T.B.T. Do, Review on "Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation", IEEE Transaction on Pattern Analysis and Machine Intelligence, 2022
J.W. Jeong, Review on "Simple and Deep Graph Convolutional Networks", ICML 2020
H.W. Kim, Review on "Knowledge Graph", Overall KG methods
Nov 18th, 2024
V.T. Hoang, Review on "Boosting Graph Contrastive Learning via Graph Contrastive Saliency", ICML 2024
T.B.T. Do, Review on "Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection", IEEE Transaction on Pattern Analysis and Machine Intelligence, 2022
Nov 11th, 2024
T.B.T. Do, Review on "Patch-Wise Graph Contrastive Learning for Image Translation", AAAI 2024
Nov 4th, 2024
V.T. Hoang, Review on "MOAT: Graph Prompting for 3D Molecular Graphs", CIKM 2024
T.B.T. Do, Review on "Topological Cycle Graph Attention Network for Brain Functional Connectivity", MICCAI 2024
J.W. Jeong, Review on "Deeper GCN: All You Need to Train Deeper GCNs", arXiv preprint arXiv:2006.07739 2020
H.C. Yang, Review on "MuSIF: A Product Recommendation System Based on Multi-source Implicit Feedback", AIAI 2019
H.W. Kim, Review on "HOW POWERFUL ARE GRAPH NEURAL NETWORKS?", ICML 2022
Oct 28th, 2024
V.T. Hoang, Review on "Shift-Robust Molecular Relational Learning with Causal Substructure", KDD 2023
T.B.T. Do, Review on "BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis", Medical Image Analysis, 2021
Oct 21st, 2024
V.T. Hoang, Review on "CHEMICAL-REACTION-AWARE MOLECULE REPRESENTATION LEARNING", ICLR 2022
T.B.T. Do, Review on "A Novel Adaptive Hypergraph Neural Network for Enhancing Medical Image Segmentation", MICCAI 2024
Oct 14th, 2024
V.T. Hoang, Review on "Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders", IJCAI 2024
T.B.T. Do, Review on "TaGAT: Topology-Aware Graph Attention Network For Multi-modal Retinal Image Fusion", MICCAI 2024
Oct 7th, 2024
V.T. Hoang, Review on "Hierarchical Generation of Molecular Graphs using Structural Motifs", ICML 2022
T.B.T. Do, Review on "GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition", ECCV 2024
Q.H. Tran, Review on "MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving", IJCAI 2024
J.H. Shim, Review on "LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation", SIGIR 2020
Sep 30th, 2024
V.T. Hoang, Review on "Molecular Contrastive LearningwithChemical Element Knowledge Graph", AAAI 2022
T.B.T. Do, Review on "ACGT-Net: Adaptive Cuckoo Refinement-Based Graph Transfer Network for Hyperspectral Image Classification", IEEE Transactions on Geoscience and Remote Sensing, 2023
Q.H. Tran, Review on "GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing", KDD 2024
J.W. Jeong, Review on "Graph Attention Networks", ICLR 2018
Sep 23rd, 2024
V.T. Hoang, Review on "ONE TRANSFORMER CAN UNDERSTAND BOTH 2D & 3D MOLECULAR DATA", ICLR 2023
T.B.T. Do, Review on "Prompt-supervised Dynamic Attention Graph Convolutional Network for Skeleton-based Action Recognition", Neurocomputing, 2024
Q.H. Tran, Review on "MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting", AAAI 2024
Sep 9th, 2024
V.T. Hoang, Review on "Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery", AAAI 2024
T.B.T. Do, Review on "Sparse Multi-Relational Graph Convolutional Network for Multi-type Object Trajectory Prediction", IJCAI 2024
Q.H. Tran, Review on "Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning", IJCAI 2023
Sep 2nd, 2024
V.T. Hoang, Review on "ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations", AAAI 2021
T.B.T. Do, Review on "MLP-DINO: Category Modeling and Query Graphing with Deep MLP for Object Detection", IJCAI 2024
Q.H. Tran, Review on "Dynamic Semantic-Based Spatial Graph Convolution Network for Skeleton-Based Human Action Recognition", AAAI 2024
Aug 26th, 2024
T.B.T. Do, Review on "Learning Graph Neural Networks for Image Style Transfer", ECCV 2022
Q.H. Tran, Review on "Self-Supervised Learning for Multilevel Skeleton-Based Forgery Detection via Temporal-Causal Consistency of Actions", AAAI 2023
Aug 19th, 2024
T.B.T. Do, Review on "Re:PolyWorld - A Graph Neural Network for Polygonal Scene Parsing", ICCV 2023
Q.H. Tran, Review on "Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling", AAAI 2023
Aug 12th, 2024
T.B.T. Do, Review on "GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation", ICCV 2023
Q.H. Tran, Review on "Spatio-Temporal Fusion for Human Action Recognition via Joint Trajectory Graph", AAAI 2024
Aug 5th, 2024
V.T. Hoang, Review on "Self-supervised Graph Learning for Recommendation", SIGIR 2021
T.B.T. Do, Review on "CheckerPose: Progressive Dense Keypoint Localization for Object Pose Estimation with Graph Neural Network", ICCV 2023
Q.H. Tran, Review on "GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks", NeurIPS 2023
Jul 29th, 2024
V.T. Hoang, Review on "Substructure Aware Graph Neural Networks", AAAI 2023
T.B.T. Do, Review on "VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering", ICCV 2023
Q.H. Tran, Review on "Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction", AAAI 2023
J.W. Jeong, Review on "Semi-Supervised Classification with Graph Convolutional Networks", ICLR 2017
Jul 22nd, 2024
V.T. Hoang, Review on "Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks", KDD 2024
T.B.T. Do, Review on "Face Clustering via Graph Convolutional Networks with Confidence Edges", ICCV 2023
Q.H. Tran, Review on "WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series", AAAI 2023
Jul 15th, 2024
V.T. Hoang, Review on "SeedGNN: Graph Neural Network for Supervised Seeded Graph Matching", ICML 2023
Q.H. Tran, Review on "M2G4RTP: A Multi-Level and Multi-Task Graph Model for Instant-Logistics Route and Time Joint Prediction", ICDE 2023
J.W. Jeong, Review on "metapath2vec: Scalable Representation Learning for Heterogeneous Networks", KDD 2017
Jul 12th, 2024
Q.H. Tran, Review on "Spatio-Temporal Neural Structural Causal Models for Bike Flow Prediction", AAAI 2023
Jul 10th, 2024
T.B.T. Do, Review on "Improving Graph Networks through Selection-based Convolution", WACV 2024
Q.H. Tran, Review on "PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction", AAAI 2023
Jul 8th, 2024
V.T. Hoang, Review on "GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels", NeurIPS 2023
T.B.T. Do, Review on "RIMeshGNN: A Rotation-Invariant Graph Neural Network for Mesh Classification", WACV 2024
Q.H. Tran, Review on "Forecasting COVID-19 Dynamics: Clustering, Generalized Spatiotemporal Attention, and Impacts of Mobility and Geographic Proximity", ICDE 2023
J.W. Jeong, Review on "struc2vec: Learning Node Representations from Structural Identity", KDD 2017
Jul 5th, 2024
T.B.T. Do, Review on "Self-Supervised Relation Alignment for Scene Graph Generation", WACV 2024
Q.H. Tran, Review on "Spatial-Temporal Graph-Based AU Relationship Learning for Facial Action Unit Detection", CVPR 2023
Jul 3rd, 2024
T.B.T. Do, Review on "GIPCOL: Graph-Injected Soft Prompting for Compositional Zero-Shot Learning", WACV 2024
Q.H. Tran, Review on "Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction", IJCAI 2024
Jul 1st, 2024
V.T. Hoang, Review on "Motif-aware Attribute Masking for Molecular Graph Pre-training", NeurIPS 2023
T.B.T. Do, Review on "G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation", WACV 2024
Q.H. Tran, Review on "TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling", AAAI 2024
Jun 28th, 2024
T.B.T. Do, Review on "Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks", IJCAI 2024
Q.H. Tran, Review on "Scalable Spatiotemporal Graph Neural Networks", AAAI 2023
Jun 27th, 2024
T.B.T. Do, Review on "GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classification", WACV 2024
Q.H. Tran, Review on "MGGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction", AAAI 2024
Jun 24th, 2024
T.B.T. Do, Review on "Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents", WACV 2024
Q.H. Tran, Review on "Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective", AAAI 2024
Jun 21st, 2024
T.B.T. Do, Review on "Vision HGNN: An Image is More than a Graph of Nodes", ICCV 2023
Q.H. Tran, Review on "Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation", AAAI 2024
Jun 19th, 2024
T.B.T. Do, Review on "A Simple Baseline for Weakly-Supervised Scene Graph Generation", ICCV 2021
Q.H. Tran, Review on "Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction", CVPR 2022
Jun 17th, 2024
V.T. Hoang, Review on "Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning", NeurIPS 2023
T.B.T. Do, Review on "A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective", arXiv preprint arXiv:2209.13232 (2022)
Q.H. Tran, Review on "Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention", IJCAI 2022
Jun 14th, 2024
T.B.T. Do, Review on "Video Matting via Consistency-Regularized Graph Neural Networks", ICCV 2021
Q.H. Tran, Review on "GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM", AAAI 2023
Jun 12th, 2024
T.B.T. Do, Review on "Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation", CVPR 2021
Jun 11th, 2024
T.B.T. Do, Review on "Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph", ECCV 2022
Jun 10th, 2024
V.T. Hoang, Review on "Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules", NeurIPS 2024
T.B.T. Do, Review on "Graph Representation Learning Meets Computer Vision: A Survey", IEEE Transactions on Artificial Intelligence, 2023
Q.H. Tran, Review on "CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting", AAAI 2022
Jun 9th, 2024
T.B.T. Do, Review on "Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud", CVPR 2020
Jun 8th, 2024
T.B.T. Do, Review on "Cascade Graph Neural Network for RGB-D Salient Object Detection", ECCV 2020
Jun 7th, 2024
T.B.T. Do, Review on "Unbiased Scene Graph Generation in Videos", CVPR 2023
Jun 3rd, 2024
V.T. Hoang, Review on "One for All: Towards Training One Graph Model for All Classification Tasks", ICLR 2024
T.B.T. Do, Review on "Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion", NeurIPS 2023
Q.H. Tran, Review on "TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking", ICCV 2023
Y.J Wu, Review on "Prefix-Tuning: Optimizing Continuous Prompts for Generation", ACL/IJCNLP 2021
May 27th, 2024
V.T. Hoang, Review on "Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering", NeurIPS 2022
T.B.T. Do, Review on "Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships", NeurIPS 2023
Q.H. Tran, Review on "Spatio-Temporal Meta-Graph Learning for Traffic Forecasting", AAAI 2023
Y.J Wu, Review on "A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks", ICLR 2019
May 20th, 2024
T.B.T. Do, Review on "G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors", CVPR 2023
Q.H. Tran, Review on "DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting", ICML 2022
Y.J Wu, Review on "LLAMA PRO: Progressive LLaMA with Block Expansion", arXiv preprint, arXiv:2401.02415, 2024
May 13th, 2024
V.T. Hoang, Review on "Universal Prompt Tuning for Graph Neural Networks", NeurIPS 2024
T.B.T. Do, Review on "Learning and Aggregating Lane Graphs for Urban Automated Driving", CVPR 2023
Q.H. Tran, Review on "Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer", KDD 2022
Y.J Wu, Review on "RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation", arXiv preprint, arXiv:2403.05313, 2024
May 6th, 2024
V.T. Hoang, Review on "GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks", WWW 2023
T.B.T. Do, Review on "Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs", CVPR 2020
Q.H. Tran, Review on "Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting", AAAI 2022
J.W. Jeong, Review on "Structural Deep Network Embedding", KDD 2016
Y.J Wu, Review on "A Survey of Techniques for Maximizing LLM Performance", OpenAI 2023
Apr 29th, 2024
V.T. Hoang, Review on "Simplifying and Empowering Transformers for Large-Graph Representations", NeurIPS 2023
T.B.T. Do, Review on "TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification", CVPR 2023
Q.H. Tran, Review on "Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction", AAAI 2023
Apr 22nd, 2024
V.T. Hoang, Review on "Large Graph Property Prediction via Graph Segment Training", NeurIPS 2021
T.B.T. Do, Review on "Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation", CVPR 2023
Q.H. Tran, Review on "Taming Local Effects in Graph-based Spatiotemporal Forecasting", NeurIPS 2023
Apr 15th, 2024
V.T. Hoang, Review on "Simple and Asymmetric Graph Contrastive Learning without Augmentations", NeurIPS 2024
T.B.T. Do, Review on "G-TAD: Sub-Graph Localization for Temporal Action Detection", CVPR 2020
Q.H. Tran, Review on "Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment", NeurIPS 2023
Y.J Wu, Review on "GLM: General Language Model Pretraining with Autoregressive Blank Infilling", ACL 2022
Apr 8th, 2024
V.T. Hoang, Review on "Weisfeiler and Lehman Go Cellular: CW Networks", NeurIPS 2021 and "Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes", AAAI 2024
T.B.T. Do, Review on "Region Graph Embedding Network for Zero-Shot Learning", ECCV 2020
Q.H. Tran, Review on "Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting", AAAI 2024
J.W. Jeong, Review on "Asymmetric Transitivity Preserving Graph Embedding", KDD 2016
Y.J Wu, Review on "Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition", ICASSP 2018
Apr 1st, 2024
V.T. Hoang, Review on "Train Once and Explain Everywhere: Pre-training Interpretable GNNs", NeurIPS 2024
T.B.T. Do, Review on "Person Re-identification using Heterogeneous Local Graph Attention Networks", CVPR 2021
Q.H. Tran, Review on "Transfer graph neural networks for pandemic forecasting", AAAI 2021
J.W. Jeong, Review on "LINE: Large-scale Information Network Embedding", WWW 2015
Y.J Wu, Review on "From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting", EMNLPw 2023
Mar 25th, 2024
V.T. Hoang, Review on "GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising", NeurIPS 2023
T.B.T. Do, Review on "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation", ICCV 2021
Q.H. Tran, Review on "Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting", AAAI 2021
J.W. Jeong, Review on "node2vec: Scalable Feature Learning for Networks", KDD 2016
Mar 18th, 2024
V.T. Hoang, Review on "Fragment-based Pretraining and Finetuning on Molecular Graphs", NeurIPS 2023
T.B.T. Do, Review on "Learning Graph Embeddings for Compositional Zero-shot Learning", CVPR 2021
Q.H. Tran, Review on "GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction", IJCAI 2019
J.W. Jeong, Review on "Attention Is All You Need", NeurIPS 2017
Mar 11th, 2024
V.T. Hoang, Review on "Contrastive Multi-View Representation Learning on Graphs", ICML 2020
T.B.T. Do, Review on "Translating Embeddings for Modeling Multi-relational Data", NeurIPS 2013
Q.H. Tran, Review on "LINE: Large-scale Information Network Embedding", WWW 2015
J.W. Jeong, Review on "Sequence to Sequence Learning with Neural Networks", NeurIPS 2014
Mar 4th, 2024
V.T. Hoang, Review on "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation", WWW 2022
T.B.T. Do, Review on "Pure Transformers are Powerful Graph Learners", NeurIPS 2022
Q.H. Tran, Review on "DeepWalk: Online Learning of Social Representations", KDD 2014
Feb 26th, 2024
T.B.T. Do, Review on "Structure-Aware Transformer for Graph Representation Learning", IEEE Transactions on Knowledge and Data Engineering, 2021
Feb 20th, 2024
T.B.T. Do, Review on "Sparse Graph Attention Networks", ICML 2022
Jan 22nd, 2024
M.S. Kim, Review on "Attention Is All You Need", NeurIPS 2017
Jan 15th, 2024
T.B.T. Do, Review on "Don't walk, skip! online learning of multi-scale network embeddings", ASONAM 2017
M.S. Kim, Review on "Attention Is All You Need", NeurIPS 2017
Jan 8th, 2024
V.T.Hoang, Review on "Coarformer: Transformer for large graph via graph coarsening", Openreview Preprint, 2022
T.B.T. Do, Review on "GraRep: Learning Graph Representations with Global Structural Information", CIKM 2015
M.S.Kim, Review on "Neural machine translation by jointly learning to align and translate", NeurIPS 2014
Jan 2nd, 2024
V.T.Hoang, Review on "Graph Inductive Biases in Transformers without Message Passing", ICML 2023
T.B.T. Do, Review on "LINE: Large-scale Information Network Embedding", WWW 2015
