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06/19/2023
Distributed Marker Representation for Ambiguous Discourse Markers and Entangled Relations
Discourse analysis is an important task because it models intrinsic sema...
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06/02/2023
Adaptive physics-informed neural networks for dynamic thermo-mechanical coupling problems in large-size-ratio functionally graded materials
In this paper, we present the adaptive physics-informed neural networks ...
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01/06/2023
Deep Biological Pathway Informed Pathology-Genomic Multimodal Survival Prediction
The integration of multi-modal data, such as pathological images and gen...
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10/06/2022
Probabilistic Model Incorporating Auxiliary Covariates to Control FDR
Controlling False Discovery Rate (FDR) while leveraging the side informa...
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07/15/2022
MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sources
Recent neural network based Direction of Arrival (DoA) estimation algori...
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02/28/2022
Variational Interpretable Learning from Multi-view Data
The main idea of canonical correlation analysis (CCA) is to map differen...
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11/09/2021
Learning Logic Rules for Document-level Relation Extraction
Document-level relation extraction aims to identify relations between en...
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07/24/2021
Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection
Smart contract vulnerability detection draws extensive attention in rece...
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01/24/2021
NeurT-FDR: Controlling FDR by Incorporating Feature Hierarchy
Controlling false discovery rate (FDR) while leveraging the side informa...
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08/18/2020
Glancing Transformer for Non-Autoregressive Neural Machine Translation
Non-autoregressive neural machine translation achieves remarkable infere...
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05/11/2020
Deep Latent Variable Model for Longitudinal Group Factor Analysis
In many scientific problems such as video surveillance, modern genomic a...
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05/11/2020
Probabilistic Canonical Correlation Analysis for Sparse Count Data
Canonical correlation analysis (CCA) is a classical and important multiv...
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04/17/2020
Active Sentence Learning by Adversarial Uncertainty Sampling in Discrete Space
In this paper, we focus on reducing the labeled data size for sentence l...
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05/25/2019
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Knowledge base is one of the main forms to represent information in a st...
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05/16/2019
Dynamically Fused Graph Network for Multi-hop Reasoning
Text-based question answering (TBQA) has been studied extensively in rec...
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09/12/2018
TGE-PS: Text-driven Graph Embedding with Pairs Sampling
In graphs with rich text information, constructing expressive graph repr...
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09/07/2018
Deep Recurrent Survival Analysis
Survival analysis is a hotspot in statistical research for modeling time...
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04/10/2018