Kishan K C

Applied Scientist, Amazon

Joined

April 2018

Names

Kishan K C (Preferred)

Kishan KC

Emails

****@rit.edu (Confirmed)

****@amazon.com (Confirmed)

****@gmail.com (Confirmed)

Personal Links

Career & Education History

Applied Scientist

Amazon (amazon.com)

2022 – Present

PhD student

Rochester Institute of Technology (rit.edu)

2016 – 2021

Advisors, Relations & Conflicts

PhD Advisor

Anne Haake

2016 – 2021

Expertise

Question Answering

2022 – Present

Document Retrieval

2022 – Present

Natural Language Processing

2021 – Present

Graph convolution networks

2017 – Present

Deep learning

2016 – Present

Network representation learning

2016 – Present

Link Prediction

2016 – Present

Bayesian Deep Learning

2016 – Present

Publications

Bayesian Neighborhood Adaptation for Graph Neural Networks
Paribesh Regmi, Rui Li, Kishan K C
- Accepted by TMLR
- Readers: Everyone
Bayesian Neighborhood Adaptation for Graph Neural Networks
Paribesh Regmi, Rui Li, Kishan K C
- Submitted to ICLR 2025
- Readers: Everyone
Joint Inference for Neural Network Depth and Dropout Regularization
Kishan K C, Rui Li, Mahdi Gilany
- Published: 09 Nov 2021, Last Modified: 05 May 2023
- NeurIPS 2021 Poster
- Readers: Everyone
Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks
Kishan KC, Rui Li, Feng Cui, Anne R. Haake
- 2020 (modified: 24 Dec 2022)
- CoRR 2020
- Readers: Everyone
Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction
Kishan KC, Feng Cui, Anne R. Haake, Rui Li
- 2020 (modified: 24 Dec 2022)
- ICPR 2020
- Readers: Everyone
GNE: a deep learning framework for gene network inference by aggregating biological information
Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne R. Haake
- 2019 (modified: 28 Feb 2023)
- BMC Syst. Biol. 2019
- Readers: Everyone

Kishan K C

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Bayesian Neighborhood Adaptation for Graph Neural Networks

Bayesian Neighborhood Adaptation for Graph Neural Networks

Joint Inference for Neural Network Depth and Dropout Regularization

Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction

GNE: a deep learning framework for gene network inference by aggregating biological information

Co-Authors