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08/21/2023
Spear and Shield: Adversarial Attacks and Defense Methods for Model-Based Link Prediction on Continuous-Time Dynamic Graphs
Real-world graphs are dynamic, constantly evolving with new interactions...
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07/14/2023
Global sensitivity analysis in the limited data setting with application to char combustion
In uncertainty quantification, variance-based global sensitivity analysi...
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03/11/2023
An approximate control variates approach to multifidelity distribution estimation
Forward simulation-based uncertainty quantification that studies the dis...
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02/17/2023
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning
The aim of continual learning is to learn new tasks continuously (i.e., ...
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01/01/2023
Graphlets over Time: A New Lens for Temporal Network Analysis
Graphs are widely used for modeling various types of interactions, such ...
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12/06/2022
Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging
We propose novel methods for Conditional Value-at-Risk (CVaR) estimation...
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06/15/2022
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations
Event cameras respond to brightness changes in the scene asynchronously ...
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06/09/2022
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs
Although machine learning on hypergraphs has attracted considerable atte...
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04/07/2022
Bi-fidelity conditional-value-at-risk estimation by dimensionally decomposed generalized polynomial chaos expansion
Digital twin models allow us to continuously assess the possible risk of...
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03/29/2022
Machine Composition of Korean Music via Topological Data Analysis and Artificial Neural Network
Common AI music composition algorithms based on artificial neural networ...
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01/30/2022
AutoSNN: Towards Energy-Efficient Spiking Neural Networks
Spiking neural networks (SNNs) that mimic information transmission in th...
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06/14/2021
Energy-efficient Knowledge Distillation for Spiking Neural Networks
Spiking neural networks (SNNs) have been gaining interest as energy-effi...
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04/22/2021
Noise-Robust Deep Spiking Neural Networks with Temporal Information
Spiking neural networks (SNNs) have emerged as energy-efficient neural n...
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02/23/2021
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams
Consider traffic data (i.e., triplets in the form of source-destination-...
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02/16/2021