Harsh Shrivastava

Orcid: 0000-0002-8366-6355

Affiliations:
  • Microsoft Research, Redmond
  • Georgia Institute of Technology, Atlanta, GA, USA (PhD 2021)


According to our database1, Harsh Shrivastava authored at least 23 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Methods for Recovering Conditional Independence Graphs: A Survey.
J. Artif. Intell. Res., 2024

Next-Token Prediction Task Assumes Optimal Data Ordering for LLM Training in Proof Generation.
CoRR, 2024

Generative Kaleidoscopic Networks.
CoRR, 2024

Methods for recovering conditional independence graphs (Abstract Reprint).
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023
Federated Learning with Neural Graphical Models.
CoRR, 2023

Knowledge Propagation over Conditional Independence Graphs.
CoRR, 2023

DiversiGATE: A Comprehensive Framework for Reliable Large Language Models.
CoRR, 2023

Are uGLAD? Time will tell!
CoRR, 2023

Neural Graph Revealers.
Proceedings of the Machine Learning for Multimodal Healthcare Data, 2023

Neural Graphical Models.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2023

MathPrompter: Mathematical Reasoning using Large Language Models.
Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

tGLAD: A Sparse Graph Recovery Based Approach for Multivariate Time Series Segmentation.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2022
GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks.
J. Comput. Biol., 2022

uGLAD: Sparse graph recovery by optimizing deep unrolled networks.
CoRR, 2022

EnGRaiN: a supervised ensemble learning method for recovery of large-scale gene regulatory networks.
Bioinform., 2022

2021
On Using Inductive Biases for Designing Deep Learning Architectures.
PhD thesis, 2021

Echo State Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
GLAD: Learning Sparse Graph Recovery.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
AntMan: Sparse Low-Rank Compression to Accelerate RNN inference.
CoRR, 2019

GLAD: Learning Sparse Graph Recovery.
CoRR, 2019

2018
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2015
Classification with imbalance: A similarity-based method for predicting respiratory failure.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015


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