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09/16/2023
Efficient Privacy-Preserving Convolutional Spiking Neural Networks with FHE
With the rapid development of AI technology, we have witnessed numerous ...
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07/12/2023
Learning Stochastic Dynamical Systems as an Implicit Regularization with Graph Neural Networks
Stochastic Gumbel graph networks are proposed to learn high-dimensional ...
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05/25/2023
On the Weisfeiler-Leman dimension of permutation graphs
It is proved that the Weisfeiler-Leman dimension of the class of permuta...
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05/09/2023
The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
We present The Vault, an open-source, large-scale code-text dataset desi...
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04/02/2023
Better Language Models of Code through Self-Improvement
Pre-trained language models for code (PLMCs) have gained attention in re...
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05/31/2022
Continuous Temporal Graph Networks for Event-Based Graph Data
There has been an increasing interest in modeling continuous-time dynami...
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05/30/2022
Stock Trading Optimization through Model-based Reinforcement Learning with Resistance Support Relative Strength
Reinforcement learning (RL) is gaining attention by more and more resear...
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07/02/2020
Decentralized Deep Reinforcement Learning for Network Level Traffic Signal Control
In this thesis, I propose a family of fully decentralized deep multi-age...
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04/01/2020
GitHub Repositories with Links to Academic Papers: Open Access, Traceability, and Evolution
Traceability between published scientific breakthroughs and their implem...
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08/20/2018
Leveraging Historical Associations between Requirements and Source Code to Identify Impacted Classes
As new requirements are introduced and implemented in a software system,...
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04/06/2018
Semantically Enhanced Software Traceability Using Deep Learning Techniques
In most safety-critical domains the need for traceability is prescribed ...
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12/12/2017
Robust Fragmentation Modeling of Hegselmann-Krause-Type Dynamics
In opinion dynamics, how to model the enduring fragmentation phenomenon ...
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11/04/2017