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Kishan K C
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Year
GNE: A deep learning framework for gene network inference by aggregating biological information
K KC, R Li, F Cui, Q Yu, A Haake
BMC Systems Biology, 2019
362019
Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches
PN Yin, K KC, S Wei, Q Yu, R Li, AR Haake, H Miyamoto, F Cui
BMC medical informatics and decision making 20 (1), 1-11, 2020
92020
Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks
K KC, R Li, F Cui, A Haake
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021
7*2021
Joint Inference for Neural Network Depth and Dropout Regularization
KC Kishan, R Li, M Gilany
Neural Information Processing Systems, 2021
1*2021
Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction
K KC, F Cui, AR Haake, R Li
International Conference on Pattern Recognition (ICPR), 7126-7133, 2021
12021
openFEAT: Improving Speaker Identification by Open-set Few-shot Embedding Adaptation with Transformer
K K C, Z Tan, L Chen, M Jin, E Han, A Stolcke, C Lee
arXiv preprint arXiv:2202.12349, 2022
2022
Scalable Probabilistic Model Selection for Network Representation Learning in Biological Network Inference
K K C
Rochester Institute of Technology, 2022
2022
Machine learning predicts nucleosome binding modes of transcription factors
K KC, SK Subramanya, R Li, F Cui
BMC Bioinformatics 22 (1), 1471-2105, 2021
2021
(Poster) Learning topology-preserving embedding for gene interaction networks
K KC, R Li, F Cui, AR Haake
17th European Conference on Computational Biology (Poster), 2018
2018
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Articles 1–9