Abhishek Sinha
Abhishek Sinha
Software engineer at Waymo
Verified email at - Homepage
Cited by
Cited by
Charting the right manifold: Manifold mixup for few-shot learning
P Mangla, N Kumari, A Sinha, M Singh, B Krishnamurthy, ...
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2020
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
Negative data augmentation
A Sinha, K Ayush, J Song, B Uzkent, H Jin, S Ermon
arXiv preprint arXiv:2102.05113, 2021
D2c: Diffusion-decoding models for few-shot conditional generation
A Sinha, J Song, C Meng, S Ermon
Advances in Neural Information Processing Systems 34, 12533-12548, 2021
Harnessing the vulnerability of latent layers in adversarially trained models
N Kumari, M Singh, A Sinha, H Machiraju, B Krishnamurthy, ...
Proceedings of the 28th International Joint Conference on Artificial …, 2019
Intelligent fault analysis in electrical power grids
B Bhattacharya, A Sinha
2017 IEEE 29th International Conference on Tools with Artificial …, 2017
Attributional robustness training using input-gradient spatial alignment
M Singh, N Kumari, P Mangla, A Sinha, VN Balasubramanian, ...
European Conference on Computer Vision, 515-533, 2020
Introspection: Accelerating neural network training by learning weight evolution
A Sinha, M Sarkar, A Mukherjee, B Krishnamurthy
arXiv preprint arXiv:1704.04959, 2017
Powering robust fashion retrieval with information rich feature embeddings
A Chopra, A Sinha, H Gupta, M Sarkar, K Ayush, B Krishnamurthy
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
Comparing distributions by measuring differences that affect decision making
S Zhao, A Sinha, Y He, A Perreault, J Song, S Ermon
International Conference on Learning Representations, 2022
On the benefits of models with perceptually-aligned gradients
G Aggarwal, A Sinha, N Kumari, M Singh
arXiv preprint arXiv:2005.01499, 2020
Neural networks in an adversarial setting and ill-conditioned weight space
A Sinha, M Singh, B Krishnamurthy
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
Generating trained neural networks with increased robustness against adversarial attacks
M Singh, N Kumari, D Khattar, B Krishnamurthy, A Sinha
US Patent 11,481,617, 2022
Introspection network for training neural networks
M Sarkar, B Krishnamurthy, A Sinha, A Mukherjee
US Patent 10,755,199, 2020
Attention based natural language grounding by navigating virtual environment
A Sinha, B Akilesh, M Sarkar, B Krishnamurthy
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 236-244, 2019
A method for computing class-wise universal adversarial perturbations
T Gupta, A Sinha, N Kumari, M Singh, B Krishnamurthy
arXiv preprint arXiv:1912.00466, 2019
Identifying digital attributes from multiple attribute groups within target digital images utilizing a deep cognitive attribution neural network
A Chopra, M Sarkar, J Dahl, H Gupta, B Krishnamurthy, A Sinha
US Patent 11,386,144, 2022
Classifying digital images in few-shot tasks based on neural networks trained using manifold mixup regularization and self-supervision
M Singh, P Mangla, N Kumari, B Krishnamurthy, A Sinha
US Patent 11,308,353, 2022
Intelligent subset selection of power generators for economic dispatch
B Bhattacharya, A Sinha
arXiv preprint arXiv:1709.02513, 2017
Deep fault analysis and subset selection in solar power grids
B Bhattacharya, A Sinha
arXiv preprint arXiv:1711.02810, 2017
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