Huichen Yang

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 17

Top Topics

Convolutional Neural Networks

Machine Learning

Scientific Literature

Information Extraction

Top Venues

Publications

Caleb Martin, Huichen Yang, William H. Hsu
KDDIE at SemEval-2023 Task 2: External Knowledge Injection for Named Entity Recognition. SemEval@ACL (2023)
Avishek Bose, Huichen Yang, Marissa Shivers, Ahat Orazgeldiyev, William H. Hsu
Context-Augmented Key Phrase Extraction from Short Texts for Cyber Threat Intelligence Tasks. ISI (2023)
Huichen Yang
PIEKM: ML-based Procedural Information Extraction and Knowledge Management System for Materials Science Literature. AACL/IJCNLP (System Demonstrations) (2022)
Reza Taherdangkoo, Miaomiao Tian, Ali Sadighi, Tao Meng, Huichen Yang, Christoph Butscher
Experimental Data on Solubility of the Two Calcium Sulfates Gypsum and Anhydrite in Aqueous Solutions. Data 7 (10) (2022)
Caleb Martin, Huichen Yang, William H. Hsu
KDDIE at SemEval-2022 Task 11: Using DeBERTa for Named Entity Recognition. SemEval@NAACL (2022)
Huichen Yang, William H. Hsu
Transformer-Based Approach for Document Layout Understanding. ICIP (2022)
Huichen Yang, William H. Hsu
Named Entity Recognition from Synthesis Procedural Text in Materials Science Domain with Attention-Based Approach. SDU@AAAI (2021)
Huichen Yang, William H. Hsu
Automatic metadata information extraction from scientific literature using deep neural networks. ICMV (2021)
Avishek Bose, Huichen Yang, William H. Hsu, Daniel Andresen
HPCGCN: A Predictive Framework on High Performance Computing Cluster Log Data Using Graph Convolutional Networks. IEEE BigData (2021)
Mohammed Tanash, Huichen Yang, Daniel Andresen, William H. Hsu
Ensemble Prediction of Job Resources to Improve System Performance for Slurm-Based HPC Systems. PEARC (2021)
Huichen Yang, William H. Hsu
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks. ICPR (2020)
Adedolapo Okanlawon, Huichen Yang, Avishek Bose, William H. Hsu, Dan Andresen, Mohammed Tanash
Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support. CoRR (2020)
Huichen Yang, William H. Hsu
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks. CoRR (2020)
Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre, Derek Christensen, Luis Bobadilla, Emily Davich, Jordan Roth, Lei Luo, Yihong Theis, Alice Lam, Thomas Yong-Jin Han, David Buttler, William H. Hsu
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. CoRR (2019)
Huichen Yang, Alice Lam, Thomas Yong-Jin Han, David Buttler, William H. Hsu, Carlos A. Aguirre, Maria F. De La Torre, Derek Christensen, Luis Bobadilla, Emily Davich, Jordan Roth, Lei Luo, Yihong Theis
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. OST@ICDAR (2019)
Mohammed Tanash, Brandon Dunn, Daniel Andresen, William H. Hsu, Huichen Yang, Adedolapo Okanlawon
Improving HPC System Performance by Predicting Job Resources via Supervised Machine Learning. PEARC (2019)
Dan Andresen, William H. Hsu, Huichen Yang, Adedolapo Okanlawon
Machine Learning for Predictive Analytics of Compute Cluster Jobs. CoRR (2018)