Aditya Balu
Aditya Balu
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Cited by
Cited by
Mechanical properties of Austenitic Stainless Steel 304L and 316L at elevated temperatures
RK Desu, HN Krishnamurthy, A Balu, AK Gupta, SK Singh
Journal of Materials Research and Technology 5 (1), 13-20, 2016
Collaborative deep learning in fixed topology networks
Z Jiang, A Balu, C Hegde, S Sarkar
Advances in Neural Information Processing Systems 30, 2017
Learning localized features in 3D CAD models for manufacturability analysis of drilled holes
S Ghadai, A Balu, S Sarkar, A Krishnamurthy
Computer Aided Geometric Design 62, 263-275, 2018
A case study of deep reinforcement learning for engineering design: Application to microfluidic devices for flow sculpting
XY Lee, A Balu, D Stoecklein, B Ganapathysubramanian, S Sarkar
Journal of Mechanical Design 141 (11), 111401, 2019
Failure and formability studies in warm deep drawing of Ti–6Al–4V alloy
N Kotkunde, AD Deole, AK Gupta, SK Singh, B Aditya
Materials & Design 60, 540-547, 2014
Optimisation of turning parameters by integrating genetic algorithm with support vector regression and artificial neural networks
AK Gupta, SC Guntuku, RK Desu, A Balu
The International Journal of Advanced Manufacturing Technology 77, 331-339, 2015
A deep learning framework for design and analysis of surgical bioprosthetic heart valves
A Balu, S Nallagonda, F Xu, A Krishnamurthy, MC Hsu, S Sarkar
Scientific reports 9 (1), 18560, 2019
Cross-gradient aggregation for decentralized learning from non-iid data
Y Esfandiari, SY Tan, Z Jiang, A Balu, E Herron, C Hegde, S Sarkar
International conference on machine learning, 3036-3046, 2021
Fast inverse design of microstructures via generative invariance networks
XY Lee, JR Waite, CH Yang, BSS Pokuri, A Joshi, A Balu, C Hegde, ...
Nature Computational Science 1 (3), 229-238, 2021
Algorithmically-consistent deep learning frameworks for structural topology optimization
J Rade, A Balu, E Herron, J Pathak, R Ranade, S Sarkar, A Krishnamurthy
Engineering Applications of Artificial Intelligence 106, 104483, 2021
Support vector regression based flow stress prediction in austenitic stainless steel 304
RK Desu, SC Guntuku, B Aditya, AK Gupta
Procedia Materials Science 6, 368-375, 2014
Decentralized deep learning using momentum-accelerated consensus
A Balu, Z Jiang, SY Tan, C Hedge, YM Lee, S Sarkar
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Flow shape design for microfluidic devices using deep reinforcement learning
XY Lee, A Balu, D Stoecklein, B Ganapathysubramanian, S Sarkar
arXiv preprint arXiv:1811.12444, 2018
Multi-level 3D CNN for learning multi-scale spatial features
S Ghadai, X Yeow Lee, A Balu, S Sarkar, A Krishnamurthy
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
NURBS-diff: A differentiable programming module for NURBS
AD Prasad, A Balu, H Shah, S Sarkar, C Hegde, A Krishnamurthy
Computer-Aided Design 146, 103199, 2022
A deep 3d convolutional neural network based design for manufacturability framework
A Balu, KG Lore, G Young, A Krishnamurthy, S Sarkar
arXiv preprint arXiv:1612.02141, 2016
An exponential strain dependent Rusinek–Klepaczko model for flow stress prediction in austenitic stainless steel 304 at elevated temperatures
AK Gupta, HN Krishnamurthy, P Puranik, SK Singh, A Balu
Journal of Materials Research and Technology 3 (4), 370-377, 2014
A fast saddle-point dynamical system approach to robust deep learning
Y Esfandiari, A Balu, K Ebrahimi, U Vaidya, N Elia, S Sarkar
Neural Networks 139, 33-44, 2021
Multi-resolution 3D convolutional neural networks for object recognition
S Ghadai, X Lee, A Balu, S Sarkar, A Krishnamurthy
arXiv preprint arXiv:1805.12254 4, 2018
NeuFENet: neural finite element solutions with theoretical bounds for parametric PDEs
B Khara, A Balu, A Joshi, S Sarkar, C Hegde, A Krishnamurthy, ...
Engineering with Computers, 1-23, 2024
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