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 | 168 | 2018 |
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 | 54 | 2020 |
Using scene graph context to improve image generation S Tripathi, A Bhiwandiwalla, A Bastidas, H Tang arXiv preprint arXiv:1901.03762, 2019 | 31 | 2019 |
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 | 14 | 2019 |
Heuristics for image generation from scene graphs S Tripathi, A Bhiwandiwalla, A Bastidas, H Tang | 8 | 2019 |
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 | 8 | 2018 |
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 | 6 | 2024 |
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 | 6 | 1801 |
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 | 5 | 2023 |
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 | 4 | 2020 |
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 | 4 | 2019 |
Uncovering Bias in Large Vision-Language Models with Counterfactuals P Howard, A Bhiwandiwalla, KC Fraser, S Kiritchenko arXiv preprint arXiv:2404.00166, 2024 | 2 | 2024 |
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 | 2 | 2023 |
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 | 2 | 2022 |
Uncovering Bias in Large Vision-Language Models at Scale with Counterfactuals P Howard, KC Fraser, A Bhiwandiwalla, S Kiritchenko arXiv preprint arXiv:2405.20152, 2024 | 1 | 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 | 1 | 2024 |
ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution S Yu, BL White, A Bhiwandiwalla, M Hinck, ML Olson, T Nguyen, V Lal arXiv preprint arXiv:2408.15993, 2024 | | 2024 |
Methods and apparatus to design and test electronics using artificial intelligence S Kundu, SN Sridhar, A Bhiwandiwalla US Patent App. 18/620,453, 2024 | | 2024 |
Why do LLaVA Vision-Language Models Reply to Images in English? M Hinck, C Holtermann, ML Olson, F Schneider, S Yu, A Bhiwandiwalla, ... arXiv preprint arXiv:2407.02333, 2024 | | 2024 |
SocialCounterfactuals: 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 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |