| RAG vs fine-tuning: Pipelines, tradeoffs, and a case study on agriculture A Balaguer, V Benara, RL de Freitas Cunha, RM Estevão Filho, T Hendry, ... arXiv e-prints, arXiv: 2401.08406, 2024 | 29 | 2024 |
| Evaluation of brain atrophy estimation algorithms using simulated ground-truth data S Sharma, V Noblet, F Rousseau, F Heitz, L Rumbach, JP Armspach Medical image analysis 14 (3), 373-389, 2010 | 27 | 2010 |
| On the estimation and correction of bias in local atrophy estimations using example atrophy simulations S Sharma, F Rousseau, F Heitz, L Rumbach, JP Armspach Computerized Medical Imaging and Graphics 37 (7-8), 538-551, 2013 | 11 | 2013 |
| Deepg2p: fusing multi-modal data to improve crop production S Sharma, A Partap, MAL Balaguer, S Malvar, R Chandra arXiv preprint arXiv:2211.05986, 2022 | 8 | 2022 |
| RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture A Gupta, A Shirgaonkar, AL Balaguer, B Silva, D Holstein, D Li, ... arXiv preprint arXiv:2401.08406, 2024 | 7 | 2024 |
| A practical approach for super-resolution using photometric stereo and graph cuts S Sharma, MV Joshi Proceedings of the 18th British Machine Vision Conference (BMVC’07), 2007 | 5 | 2007 |
| A practical approach for simultaneous estimation of light source position, scene structure, and blind restoration using photometric observations S Sharma, MV Joshi EURASIP Journal on Advances in Signal Processing 2008, 1-12, 2008 | 4 | 2008 |
| Knowledge Guided Representation Learning and Causal Structure Learning in Soil Science S Sharma, S Sharma, L Liu, R Tushir, A Neal, R Ness, J Crawford, ... arXiv preprint arXiv:2306.09302, 2023 | 1 | 2023 |
| Causal Modeling of Soil Processes for Improved Generalization S Sharma, S Sharma, A Neal, S Malvar, E Rodrigues, J Crawford, ... arXiv preprint arXiv:2211.05675, 2022 | 1 | 2022 |
| A Graph-based Spatiotemporal Model for Energy Markets S Sharma, S Iyengar, S Zheng, K Kapoor, W Cao, J Bian, ... Proceedings of the 31st ACM International Conference on Information …, 2022 | 1 | 2022 |
| Machine learning solution to predict protein characteristics S Malvar, AKP Bhagavathula, R Chandra, MA de LUIS BALAGUER, ... US Patent App. 18/146,123, 2024 | | 2024 |
| Data driven approaches to improve understanding of process-based models and decision making S Sharma, S Sharma, EM Kiciman, R Chandra, S Malvar, ER Rodrigues US Patent App. 18/163,156, 2024 | | 2024 |
| Domain Adaptation for Sustainable Soil Management using Causal and Contrastive Constraint Minimization S Sharma, S Sharma, R Padilha, E Kiciman, R Chandra arXiv preprint arXiv:2401.07175, 2024 | | 2024 |
| Deep learning system and method for predicting crop characteristics RLDF Cunha, A Badam, PB Buehler, R Chandra, D Dan, ... US Patent App. 18/056,677, 2023 | | 2023 |
| Time-shifting optimizations for resource generation and dispatch P Kumar, A Sadeghi, S Iyengar, SA NOGHABI, S Kalyanaraman, ... US Patent App. 17/742,380, 2023 | | 2023 |
| Spatio-temporal graph neural network for time series prediction S Sharma, S Iyengar, K Kapoor, S Zheng, W Cao, J Bian, ... US Patent App. 18/046,013, 2023 | | 2023 |
| Optimization and decision-making using causal aware machine learning models trained from simulators EM Kiciman, Q Zhang, C Zhang, S Sharma, D Yuhao, R Chandra US Patent App. 17/531,700, 2023 | | 2023 |
| Knowledge Guided Representation Learning and Causal Structure Learning S Sharma, R Tushir, AL Neal, R Ness, V Kumar, JW Crawford, E Kiciman, ... 29th Association for Computing Machinery SIGKDD conference on knowledge …, 2023 | | 2023 |
| Causal Modeling of Soil Processes for Improved Generalization AL Neal, S Sharma, JW Crawford, E Kiciman, S Malvar, E Rodriguez, ... NeurIPS 2022, 2022 | | 2022 |
| Machine learning can guide experimental approaches for protein digestibility estimations S Malvar, A Bhagavathula, MAL Balaguer, S Sharma, R Chandra arXiv preprint arXiv:2211.00625, 2022 | | 2022 |
