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Satya Narayan Shukla
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2020 – today
- 2024
- [c10]Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa:
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. ACL (1) 2024: 749-775 - [c9]Kanchana Ranasinghe, Satya Narayan Shukla, Omid Poursaeed, Michael S. Ryoo, Tsung-Yu Lin:
Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs. CVPR 2024: 12977-12987 - [i14]Kanchana Ranasinghe, Satya Narayan Shukla, Omid Poursaeed, Michael S. Ryoo, Tsung-Yu Lin:
Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs. CoRR abs/2404.07449 (2024) - 2023
- [c8]Mohamed Afham, Satya Narayan Shukla, Omid Poursaeed, Pengchuan Zhang, Ashish Shah, Sernam Lim:
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding. ICCV (Workshops) 2023: 1181-1186 - [i13]Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa:
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. CoRR abs/2308.16884 (2023) - [i12]Mohamed Afham, Satya Narayan Shukla, Omid Poursaeed, Pengchuan Zhang, Ashish Shah, Sernam Lim:
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding. CoRR abs/2309.11569 (2023) - [i11]Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim:
Universal Pyramid Adversarial Training for Improved ViT Performance. CoRR abs/2312.16339 (2023) - 2022
- [c7]Satya Narayan Shukla, Benjamin M. Marlin:
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series. ICLR 2022 - 2021
- [c6]Satya Narayan Shukla, Benjamin M. Marlin:
Multi-Time Attention Networks for Irregularly Sampled Time Series. ICLR 2021 - [c5]Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter:
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. KDD 2021: 1461-1469 - [i10]Satya Narayan Shukla, Benjamin M. Marlin:
Multi-Time Attention Networks for Irregularly Sampled Time Series. CoRR abs/2101.10318 (2021) - [i9]Satya Narayan Shukla, Benjamin M. Marlin:
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series. CoRR abs/2107.11350 (2021) - 2020
- [i8]Meet P. Vadera, Satya Narayan Shukla, Brian Jalaian, Benjamin M. Marlin:
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification. CoRR abs/2002.02842 (2020) - [i7]Satya Narayan Shukla, Benjamin M. Marlin:
Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction. CoRR abs/2003.11059 (2020) - [i6]Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter:
Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes. CoRR abs/2007.07210 (2020) - [i5]Anit Kumar Sahu, Satya Narayan Shukla, J. Zico Kolter:
Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks. CoRR abs/2010.04205 (2020) - [i4]Satya Narayan Shukla, Benjamin M. Marlin:
A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance. CoRR abs/2012.00168 (2020)
2010 – 2019
- 2019
- [c4]Satya Narayan Shukla, Benjamin M. Marlin:
Interpolation-Prediction Networks for Irregularly Sampled Time Series. ICLR (Poster) 2019 - [i3]Satya Narayan Shukla, Benjamin M. Marlin:
Interpolation-Prediction Networks for Irregularly Sampled Time Series. CoRR abs/1909.07782 (2019) - [i2]Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott, J. Zico Kolter:
Black-box Adversarial Attacks with Bayesian Optimization. CoRR abs/1909.13857 (2019) - 2018
- [i1]Satya Narayan Shukla, Benjamin M. Marlin:
Modeling Irregularly Sampled Clinical Time Series. CoRR abs/1812.00531 (2018) - 2017
- [c3]Satya Narayan Shukla:
Estimation of blood pressure from non-invasive data. EMBC 2017: 1772-1775 - [c2]Abhishek Sengupta, A. P. Prathosh, Satya Narayan Shukla, Vaibhav Rajan, Chandan K. Reddy:
Prediction and imputation in irregularly sampled clinical time series data using hierarchical linear dynamical models. EMBC 2017: 3660-3663 - 2015
- [c1]Satya Narayan Shukla, Karan Kakwani, Amit Patra, Bipin Kumar Lahkar, Vivek Kumar Gupta, Alwar Jayakrishna, Puneet Vashisht, Induja Sreekanth:
Noninvasive Cuffless Blood Pressure Measurement by Vascular Transit Time. VLSID 2015: 535-540
Coauthor Index
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