Kishan K C
Kishan K C
Applied Scientist at Amazon Alexa AI
Verified email at - Homepage
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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
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
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
Joint Inference for Neural Network Depth and Dropout Regularization
K KC, R Li, M Gilany
Neural Information Processing Systems, 2021
OpenFEAT: Improving Speaker Identification by Open-Set Few-Shot Embedding Adaptation with Transformer
K KC, Z Tan, L Chen, M Jin, E Han, A Stolcke, C Lee
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
Efficient fine-tuning large language models for knowledge-aware response planning
M Nguyen, KC Kishan, T Nguyen, A Chadha, T Vu
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
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
Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks
K KC, R Li, P Regmi, AR Haake
arXiv preprint arXiv:2211.13231, 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
Question-context alignment and answer-context dependencies for effective answer sentence selection
M Van Nguyen, K KC, T Nguyen, TH Nguyen, A Chadha, T Vu
arXiv preprint arXiv:2306.02196, 2023
Scalable Probabilistic Model Selection for Network Representation Learning in Biological Network Inference
Rochester Institute of Technology, 2022
(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
Supplementary Material for Joint Inference for Neural Network Depth and Dropout Regularization
KC Kishan, R Li, M Gilany
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