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Harsh Shrivastava
Harsh Shrivastava
Microsoft Research, Redmond
Adresse e-mail validée de microsoft.com - Page d'accueil
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Mathprompter: Mathematical reasoning using large language models
S Imani, L Du, H Shrivastava
arXiv preprint arXiv:2303.05398, 2023
2942023
ICU mortality prediction: a classification algorithm for imbalanced datasets
S Bhattacharya, V Rajan, H Shrivastava
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
912017
GLAD: Learning sparse graph recovery
H Shrivastava, X Chen, B Chen, G Lan, S Aluru, H Liu, L Song
arXiv preprint arXiv:1906.00271, 2019
462019
Classification with imbalance: A similarity-based method for predicting respiratory failure
H Shrivastava, V Huddar, S Bhattacharya, V Rajan
2015 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2015
392015
GRNUlar: a deep learning framework for recovering Single-Cell gene regulatory networks
H Shrivastava, X Zhang, L Song, S Aluru
Journal of Computational Biology 29 (1), 27-44, 2022
272022
Echo state speech recognition
H Shrivastava, A Garg, Y Cao, Y Zhang, T Sainath
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
272021
System and method for predicting health condition of a patient
H Shrivastava, V Huddar, S Bhattacharya, V Rajan
US Patent 11,087,879, 2021
232021
EnGRaiN: a supervised ensemble learning method for recovery of large-scale gene regulatory networks
M Aluru, H Shrivastava, SP Chockalingam, S Shivakumar, S Aluru
Bioinformatics 38 (5), 1312-1319, 2022
212022
Methods and systems for predicting mortality of a patient
S Bhattacharya, V Rajan, H Shrivastava
US Patent 10,463,312, 2019
162019
Neural graphical models
H Shrivastava, U Chajewska
European Conference on Symbolic and Quantitative Approaches with Uncertainty …, 2023
142023
Grnular: gene regulatory network reconstruction using unrolled algorithm from single cell rna-sequencing data
H Shrivastava, X Zhang, S Aluru, L Song
bioRxiv, 2020.04. 23.058149, 2020
142020
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
H Shrivastava, E Bart, B Price, H Dai, B Dai, S Aluru
Advances in Neural Information Processing Systems 31, 2018
142018
Methods for recovering conditional independence graphs: a survey
H Shrivastava, U Chajewska
Journal of Artificial Intelligence Research 80, 593-612, 2024
132024
uGLAD: sparse graph recovery by optimizing deep unrolled networks
H Shrivastava, U Chajewska, R Abraham, X Chen
arXiv preprint arXiv:2205.11610, 2022
132022
A deep learning approach to recover conditional independence graphs
H Shrivastava, U Chajewska, R Abraham, X Chen
NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022
122022
On Using Inductive Biases for Designing Deep Learning Architectures.
H Shrivastava
Georgia Institute of Technology, Atlanta, GA, USA, 2021
122021
Neural graph revealers
H Shrivastava, U Chajewska
Workshop on Machine Learning for Multimodal Healthcare Data, 7-25, 2023
82023
AntMan: sparse low-rank compression to accelerate RNN inference
S Rajbhandari, H Shrivastava, Y He
arXiv preprint arXiv:1910.01740, 2019
82019
Exploring entities of interest over multiple data sources using knowledge graphs
S Panda, H Shrivastava
US Patent App. 17/729,957, 2023
32023
[Industry] MathPrompter: Mathematical Reasoning using Large Language Models
S Imani, L Du, H Shrivastava
The 61st Annual Meeting Of The Association For Computational Linguistics, 2023
22023
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