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09/19/2023
TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions
Many real-world datasets are represented as tensors, i.e., multi-dimensi...
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02/10/2023
Characterization of Simplicial Complexes by Counting Simplets Beyond Four Nodes
Simplicial complexes are higher-order combinatorial structures which hav...
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02/09/2023
NeuKron: Constant-Size Lossy Compression of Sparse Reorderable Matrices and Tensors
Many real-world data are naturally represented as a sparse reorderable m...
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11/26/2022
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning
Continual Learning (CL) is the process of learning ceaselessly a sequenc...
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10/20/2022
Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data
Recently, many deep-learning techniques have been applied to various wea...
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02/17/2022
Effective Training Strategies for Deep-learning-based Precipitation Nowcasting and Estimation
Deep learning has been successfully applied to precipitation nowcasting....
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12/10/2021
SLUGGER: Lossless Hierarchical Summarization of Massive Graphs
Given a massive graph, how can we exploit its hierarchical structure for...
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06/11/2021
Learning to Pool in Graph Neural Networks for Extrapolation
Graph neural networks (GNNs) are one of the most popular approaches to u...
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06/17/2020
Incremental Lossless Graph Summarization
Given a fully dynamic graph, represented as a stream of edge insertions ...
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06/01/2020
SSumM: Sparse Summarization of Massive Graphs
Given a graph G and the desired size k in bits, how can we summarize G w...
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03/04/2020
Hypergraph Motifs: Concepts, Algorithms, and Discoveries
Hypergraphs naturally represent group interactions, which are omnipresen...
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01/24/2020