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Anahita Bhiwandiwalla
Anahita Bhiwandiwalla
Intel Corporation, Columbia University
Verified email at intel.com
Title
Cited by
Cited by
Year
Intel ngraph: An intermediate representation, compiler, and executor for deep learning
S Cyphers, AK Bansal, A Bhiwandiwalla, J Bobba, M Brookhart, ...
arXiv preprint arXiv:1801.08058, 2018
1632018
Shifted and squeezed 8-bit floating point format for low-precision training of deep neural networks
L Cambier, A Bhiwandiwalla, T Gong, M Nekuii, OH Elibol, H Tang
arXiv preprint arXiv:2001.05674, 2020
472020
Using scene graph context to improve image generation
S Tripathi, A Bhiwandiwalla, A Bastidas, H Tang
arXiv preprint arXiv:1901.03762, 2019
322019
Prediction of GNSS Phase Scintillations: A Machine Learning Approach
AB Kara Lamb, Garima Malhotra, Athanasios Vlontzos, Edward Wagstaff, Atılım ...
arXiv preprint arXiv:1910.01570, 2019
122019
Heuristics for image generation from scene graphs
S Tripathi, A Bhiwandiwalla, A Bastidas, H Tang
82019
Intel nGraph: An Intermediate Representation, Compiler, and Executor for Deep Learning. CoRR abs/1801.08058 (2018)
S Cyphers, AK Bansal, A Bhiwandiwalla, J Bobba, M Brookhart, ...
arXiv preprint arXiv:1801.08058, 2018
82018
Intel ngraph: An intermediate representation, compiler, and executor for deep learning. ArXiv. 2018
S Cyphers, AK Bansal, A Bhiwandiwalla, J Bobba, M Brookhart, ...
arXiv preprint arXiv:1801.08058, 1801
61801
Correlation of auroral dynamics and GNSS scintillation with an autoencoder
K Lamb, G Malhotra, A Vlontzos, E Wagstaff, AG Baydin, A Bhiwandiwalla, ...
arXiv preprint arXiv:1910.03085, 2019
42019
Methods and apparatus for low precision training of a machine learning model
L Cambier, A Bhiwandiwalla, T Gong
US Patent App. 16/832,830, 2020
32020
ManagerTower: Aggregating the insights of uni-modal experts for vision-language representation learning
X Xu, B Li, C Wu, SY Tseng, A Bhiwandiwalla, S Rosenman, V Lal, W Che, ...
arXiv preprint arXiv:2306.00103, 2023
22023
Probing and Mitigating Intersectional Social Biases in Vision-Language Models with Counterfactual Examples
P Howard, A Madasu, T Le, GL Moreno, A Bhiwandiwalla, V Lal
arXiv preprint arXiv:2312.00825, 2023
12023
Apparatus, articles of manufacture, and methods for composable machine learning compute nodes
E Nurvitadhi, R Poornachandran, A Davare, N Jain, C Lacewell, ...
US Patent App. 17/558,284, 2022
12022
LVLM-Intrepret: An Interpretability Tool for Large Vision-Language Models
GBM Stan, RY Rohekar, Y Gurwicz, ML Olson, A Bhiwandiwalla, E Aflalo, ...
arXiv preprint arXiv:2404.03118, 2024
2024
LVLM-Intrepret: An Interpretability Tool for Large Vision-Language Models
G Ben Melech Stan, R Yehezkel Rohekar, Y Gurwicz, ML Olson, ...
arXiv e-prints, arXiv: 2404.03118, 2024
2024
Uncovering Bias in Large Vision-Language Models with Counterfactuals
P Howard, A Bhiwandiwalla, KC Fraser, S Kiritchenko
arXiv preprint arXiv:2404.00166, 2024
2024
Methods, systems, articles of manufacture and apparatus to optimize resources in edge networks
N Jain, R Poornachandran, E Nurvitadhi, A Bhiwandiwalla, JP Munoz, ...
US Patent App. 18/039,166, 2024
2024
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks
A Madasu, A Bhiwandiwalla, V Lal
arXiv preprint arXiv:2310.04914, 2023
2023
Methods and apparatus for dynamic xpu hardware-aware deep learning model management
R Iyer, N Jain, J Munoz, E Nurvitadhi, A Bhiwandiwalla, ...
US Patent App. 17/645,742, 2022
2022
Methods and apparatus for data enhanced automated model generation
CW Lacewell, JP Muñoz, R Poornachandran, N Jain, A Bhiwandiwalla, ...
US Patent App. 17/559,730, 2022
2022
Layout Composition from Attributed Scene Graphs
S Tripathi, A Bhiwandiwalla
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