LoG

Keyphrases

Publications

2022

Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG (2022)
Simone Piaggesi, André Panisson, Giovanni Petri
Effective Higher-Order Link Prediction and Reconstruction From Simplicial Complex Embeddings. LoG (2022)
Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Muhan Zhang, Xueqi Cheng
Towards Efficient and Expressive GNNs for Graph Classification via Subgraph-Aware Weisfeiler-Lehman. LoG (2022)
Alexandru Cristian Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie
A Systematic Evaluation of Node Embedding Robustness. LoG (2022)
Andreea Deac, Marc Lackenby, Petar Velickovic
Expander Graph Propagation. LoG (2022)
Kenza Amara, Zhitao Ying, Zitao Zhang, Zhichao Han, Yang Zhao, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang
GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. LoG (2022)
Simon Zhang, Soham Mukherjee, Tamal K. Dey
GEFL: Extended Filtration Learning for Graph Classification. LoG (2022)
Christoffel Doorman, Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Dynamic Network Reconfiguration for Entropy Maximization Using Deep Reinforcement Learning. LoG (2022)
Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu
A Survey on Deep Graph Generation: Methods and Applications. LoG (2022)
Xuhong Wang, Sirui Chen, Yixuan He, Minjie Wang, Quan Gan, Junchi Yan
CEP3: Community Event Prediction With Neural Point Process on Graph. LoG (2022)
Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang
Label-Wise Graph Convolutional Network for Heterophilic Graphs. LoG (2022)
Yacouba Kaloga, Pierre Borgnat, Amaury Habrard
A Simple Way to Learn Metrics Between Attributed Graphs. LoG (2022)
Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh V. Chawla
FakeEdge: Alleviate Dataset Shift in Link Prediction. LoG (2022)
Maciej Besta, Patrick Iff, Florian Scheidl, Kazuki Osawa, Nikoli Dryden, Michal Podstawski, Tiancheng Chen, Torsten Hoefler
Neural Graph Databases. LoG (2022)
Yixuan He, Michael Perlmutter, Gesine Reinert, Mihai Cucuringu
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian. LoG (2022)
Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
Taxonomy of Benchmarks in Graph Representation Learning. LoG (2022)
Guangxuan Xiao, Leslie Pack Kaelbling, Jiajun Wu, Jiayuan Mao
Sparse and Local Networks for Hypergraph Reasoning. LoG (2022)
Han Gao, Xu Han, Jiaoyang Huang, Jian-Xun Wang, Liping Liu
PatchGT: Transformer Over Non-Trainable Clusters for Learning Graph Representations. LoG (2022)
Donato Crisostomi, Simone Antonelli, Valentino Maiorca, Luca Moschella, Riccardo Marin, Emanuele Rodolà
Metric Based Few-Shot Graph Classification. LoG (2022)
Euan Ong, Petar Velickovic
Learnable Commutative Monoids for Graph Neural Networks. LoG (2022)
Jase Clarkson, Mihai Cucuringu, Andrew Elliott, Gesine Reinert
DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series. LoG (2022)
Tuan Le, Frank Noé, Djork-Arné Clevert
Representation Learning on Biomolecular Structures Using Equivariant Graph Attention. LoG (2022)
Yixuan He, Gesine Reinert, Mihai Cucuringu
DIGRAC: Digraph Clustering Based on Flow Imbalance. LoG (2022)
Tong Zhao, Xianfeng Tang, Danqing Zhang, Haoming Jiang, Nikhil Rao, Yiwei Song, Pallav Agrawal, Karthik Subbian, Bing Yin, Meng Jiang
AutoGDA: Automated Graph Data Augmentation for Node Classification. LoG (2022)
Adrián Arnaiz-Rodríguez, Ahmed Begga, Francisco Escolano, Nuria Oliver
DiffWire: Inductive Graph Rewiring via the Lovász Bound. LoG (2022)
Sayak Mukherjee, Sai Pushpak Nandanoori, Sheng Guan, Khushbu Agarwal, Subhrajit Sinha, Soumya Kundu, Seemita Pal, Yinghui Wu, Draguna L. Vrabie, Sutanay Choudhury
Learning Distributed Geometric Koopman Operator for Sparse Networked Dynamical Systems. LoG (2022)
Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei
Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks. LoG (2022)
Sara Hahner, Felix Kerkhoff, Jochen Garcke
Transfer Learning Using Spectral Convolutional Autoencoders on Semi-Regular Surface Meshes. LoG (2022)
Xiyuan Wang, Muhan Zhang
Graph Neural Network With Local Frame for Molecular Potential Energy Surface. LoG (2022)
Lisi Qarkaxhija, Vincenzo Perri, Ingo Scholtes
De Bruijn Goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs. LoG (2022)
Valentina Giunchiglia, Chirag Varun Shukla, Guadalupe Gonzalez, Chirag Agarwal
Towards Training GNNs Using Explanation Directed Message Passing. LoG (2022)
Johannes Gasteiger, Chendi Qian, Stephan Günnemann
Influence-Based Mini-Batching for Graph Neural Networks. LoG (2022)
Ruochen Yang, Frederic Sala, Paul Bogdan
Efficient Representation Learning for Higher-Order Data With Simplicial Complexes. LoG (2022)
Mohammad Sabbaqi, Riccardo Taormina, Alan Hanjalic, Elvin Isufi
Graph-Time Convolutional Autoencoders. LoG (2022)
Chenhui Deng, Xiuyu Li, Zhuo Feng, Zhiru Zhang
GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks. LoG (2022)
Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Joseph Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic
A Generalist Neural Algorithmic Learner. LoG (2022)
Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah
Flashlight: Scalable Link Prediction With Effective Decoders. LoG (2022)
Ralph Abboud, Radoslav Dimitrov, Ismail Ilkan Ceylan
Shortest Path Networks for Graph Property Prediction. LoG (2022)
Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yu Guang Wang
Well-Conditioned Spectral Transforms for Dynamic Graph Representation. LoG (2022)
Zhenwei Dai, Vasileios Ioannidis, Soji Adeshina, Zak Jost, Christos Faloutsos, George Karypis
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning. LoG (2022)
Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Zhitao Ying, Jure Leskovec, Pietro Liò
Learning Graph Search Heuristics. LoG (2022)
Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification. LoG (2022)
Abdulkadir Çelikkanat, Nikolaos Nakis, Morten Mørup
Piecewise-Velocity Model for Learning Continuous-Time Dynamic Node Representations. LoG (2022)
Christopher Blöcker, Jelena Smiljanic, Ingo Scholtes, Martin Rosvall
Similarity-Based Link Prediction From Modular Compression of Network Flows. LoG (2022)
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG (2022)
Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang
Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. LoG (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG (2022)
Petar Velickovic, Matko Bosnjak, Thomas Kipf, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell
Reasoning-Modulated Representations. LoG (2022)
Paul Scherer, Pietro Liò, Mateja Jamnik
Distributed Representations of Graphs for Drug Pair Scoring. LoG (2022)

volume 198, 2022

Learning on Graphs Conference, LoG 2022, 9-12 December 2022, Virtual Event. LoG 198 (2022)