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Kishlay Jha

Showing results (1-10 of 12) with videos related to

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Bioinformatics (Oxford, England)|September 23, 2021
Continual knowledge infusion into pre-trained biomedical language modelsKishlay Jha, Aidong Zhang
Advances in Knowledge Discovery and Data Mining : ... Pacific-Asia Conference, PAKDD ..., Proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining|December 26, 2025
Semantic Knowledge Augmented Hypergraph Contrastive Representation Learning for Zero-Shot Biomedical Text ClassificationRatri Mukherjee, Kishlay Jha
Proceedings. IEEE International Conference on Bioinformatics and Biomedicine|March 19, 2025
Context-Aware Contrastive Representation Learning for Zero-Shot Biomedical Text ClassificationRatri Mukherjee, Kishlay Jha
Bioinformatics (Oxford, England)|February 3, 2021
Continual representation learning for evolving biomedical bipartite networksKishlay Jha, Guangxu Xun, Aidong Zhang
Journal of Biomedical Informatics|March 13, 2019
A survey on literature based discovery approaches in biomedical domainVishrawas Gopalakrishnan, Kishlay Jha, Wei Jin, et al.
Proceedings. IEEE International Conference on Healthcare Informatics|March 20, 2025
Learning to Rank Complex Biomedical Hypotheses for Accelerating Scientific DiscoveryJuncheng Ding, Shailesh Dahal, Bijaya Adhikari, et al.
Bioinformatics (Oxford, England)|March 10, 2019
MeSHProbeNet: a self-attentive probe net for MeSH indexingGuangxu Xun, Kishlay Jha, Ye Yuan, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|May 26, 2025
Boosting Social Determinants of Health Extraction with Semantic Knowledge Augmented Large Language ModelLei Gong, Jaren Bresnick, Aidong Zhang, et al.
Bioinformatics (Oxford, England)|January 3, 2018
Towards self-learning based hypotheses generation in biomedical text domainVishrawas Gopalakrishnan, Kishlay Jha, Guangxu Xun, et al.
Knowledge and Information Systems|May 20, 2026
Automated biomedical hypothesis generation with time-aware hypergraph contrastive learningAmir Hassan Shariatmadari, Sikun Guo, Nathan C Sheffield, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|September 23, 2021
Continual knowledge infusion into pre-trained biomedical language modelsKishlay Jha, Aidong Zhang
Advances in Knowledge Discovery and Data Mining : ... Pacific-Asia Conference, PAKDD ..., Proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining|December 26, 2025
Semantic Knowledge Augmented Hypergraph Contrastive Representation Learning for Zero-Shot Biomedical Text ClassificationRatri Mukherjee, Kishlay Jha
Proceedings. IEEE International Conference on Bioinformatics and Biomedicine|March 19, 2025
Context-Aware Contrastive Representation Learning for Zero-Shot Biomedical Text ClassificationRatri Mukherjee, Kishlay Jha
Bioinformatics (Oxford, England)|February 3, 2021
Continual representation learning for evolving biomedical bipartite networksKishlay Jha, Guangxu Xun, Aidong Zhang
Journal of Biomedical Informatics|March 13, 2019
A survey on literature based discovery approaches in biomedical domainVishrawas Gopalakrishnan, Kishlay Jha, Wei Jin, et al.
Proceedings. IEEE International Conference on Healthcare Informatics|March 20, 2025
Learning to Rank Complex Biomedical Hypotheses for Accelerating Scientific DiscoveryJuncheng Ding, Shailesh Dahal, Bijaya Adhikari, et al.
Bioinformatics (Oxford, England)|March 10, 2019
MeSHProbeNet: a self-attentive probe net for MeSH indexingGuangxu Xun, Kishlay Jha, Ye Yuan, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|May 26, 2025
Boosting Social Determinants of Health Extraction with Semantic Knowledge Augmented Large Language ModelLei Gong, Jaren Bresnick, Aidong Zhang, et al.
Bioinformatics (Oxford, England)|January 3, 2018
Towards self-learning based hypotheses generation in biomedical text domainVishrawas Gopalakrishnan, Kishlay Jha, Guangxu Xun, et al.
Knowledge and Information Systems|May 20, 2026
Automated biomedical hypothesis generation with time-aware hypergraph contrastive learningAmir Hassan Shariatmadari, Sikun Guo, Nathan C Sheffield, et al.
Pageof 2