Apurva Narayan

发表

Risk-averse stochastic programming approach for microgrid planning under uncertainty

K. Ponnambalam, Apurva Narayan, 2017 .

Learning Graph Dynamics using Deep Neural Networks

Apurva Narayan, P. Roe, 2018 .

1 Spatial Dependence Modeling of Wind Resource under 2 Uncertainty Using C-Vine Copulas and Its Impact on 3 Solar-Wind Energy Co-Generation 4

K. Ponnambalam, S. Pagsuyoin, Apurva Narayan, 2017 .

Fecal microbiota transplantation efficacy for Clostridium difficile infection: A trans-kingdom battle between donor and recipient gut microbiomes

G. Wong, D. Kao, Apurva Narayan, 2020, bioRxiv.

The trans-kingdom battle between donor and recipient gut microbiome influences fecal microbiota transplantation outcome

G. Wong, D. Kao, Apurva Narayan, 2020, Scientific Reports.

HyperBox: A Supervised Approach for Hypernym Discovery using Box Embeddings

Apurva Narayan, Maulik Parmar, 2022, LREC.

System Call Logs with Natural Random Faults : Experimental Design and Application

G. M. Tchamgoue, S. Fischmeister, Yogi Joshi, 2017 .

Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey

Apurva Narayan, Abhijith Sharma, Yijun Bian, 2022, ArXiv.

Light Weight Dilated CNN for Time Series Classification and Prediction

Apurva Narayan, P. Khanna, 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Improved Sampling Strategy for Representative Set Construction

Irving K. Barber, Apurva Narayan, Kusum Sarkar, 2022 .

Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey

Apurva Narayan, Abhijith Sharma, Yijun Bian, 2022, ArXiv.

Novel Representative Sampling for Improved Active Learning

Apurva Narayan, Debangsha Sarkar, Amir Shabani, 2022, IFAC-PapersOnLine.

Spatial Dependence Modeling of Wind Resource under Uncertainty Using C-Vine Copulas and Its Impact on Solar-Wind Energy Co-Generation

K. Ponnambalam, S. Pagsuyoin, Apurva Narayan, 2017 .

Deep Learning for System Trace Restoration

Sebastian Fischmeister, Matthias Schonlau, Apurva Narayan, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Making costly manufacturing smart with transfer learning under limited data: A case study on composites autoclave processing

Abbas S. Milani, Rudolf Seethaler, Bryn Crawford, 2021, Journal of Manufacturing Systems.

Leveraging spatio-temporal features to forecast time-to-accident

Apurva Narayan, Beiyu Lin, Taif Anjum, 2022, SIGSPATIAL/GIS.

Vulnerability of CNNs against Multi-Patch Attacks

Apurva Narayan, Abhijith Sharma, Yijun Bian, 2023, SAT-CPS@CODASPY.

Long short term memory networks for short-term electric load forecasting

Keith W. Hipel, Apurva Narayan, K. Hipel, 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Is Timing Critical to Trace Reconstruction?

Javier Perez Tobia, Apurva Narayan, 2021, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

A Data-driven Multi-fidelity Physics-informed Learning Framework for Smart Manufacturing: A Composites Processing Case Study

Mehrtash Harandi, A. Milani, Apurva Narayan, 2022, 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS).

A Framework For Microgrid Planning Using Multidisciplinary Design Optimization

Apurva Narayan, Apurva Narayan, 2015 .

Improving imbalanced dataset classification using Conditional Classifier-Generator (cCGen)

Javier Perez Tobia, A. Milani, Apurva Narayan, 2022, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Spiking Approximations of the MaxPooling Operation in Deep SNNs

B. Tripp, Apurva Narayan, Ramashish Gaurav, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

A Neural Word Embedding Approach to System Trace Reconstruction

Apurva Narayan, Karuna Lakhani, Apurva Narayan, 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

Introducing Diversity In Feature Scatter Adversarial Training Via Synthesis

Apurva Narayan, Satyadwyoom Kumar, 2022, 2022 26th International Conference on Pattern Recognition (ICPR).

Self-Attention Mechanism in GANs for Molecule Generation

Apurva Narayan, S. Chinnareddy, Pranav Grandhi, 2021, 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).

Mining Time for Timed Regular Specifications

Sebastian Fischmeister, Apurva Narayan, S. Fischmeister, 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

GWAD: Greedy Workflow Graph Anomaly Detection Framework for System Traces

Apurva Narayan, Yohen Thounaojam, Wiliam Setiawan, 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

MA2DF: A Multi-Agent Anomaly Detection Framework

Apurva Narayan, Yohen Thounaojam, Wiliam Setiawan, 2020, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Assist Is Just as Important as the Goal: Image Resurfacing to Aid Model’s Robust Prediction

Apurva Narayan, Abhijith Sharma, Phil Munz, 2023, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

NSA: Naturalistic Support Artifact to Boost Network Confidence

Apurva Narayan, Abhijith Sharma, Phil Munz, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

QMine: A Framework for Mining Quantitative Regular Expressions from System Traces

Pradeep K. Mahato, Apurva Narayan, Apurva Narayan, 2020, 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C).

Enhanced Quantum Evolutionary Algorithms for Difficult Knapsack Problems

Chellapilla Patvardhan, Anand Srivastav, Apurva Narayan, 2007, PReMI.

An Active Transfer Learning (ATL) Framework for Smart Manufacturing with Limited Data: Case Study on Material Transfer in Composites Processing

Abbas S. Milani, Rudolf Seethaler, Apurva Narayan, 2021, 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS).