| Generative models for graph-based protein design J Ingraham, VK Garg, R Barzilay, T Jaakkola Advances in Neural Information Processing Systems, 2019 | 491 | 2019 |
| Generalization and representational limits of graph neural networks V Garg, S Jegelka, T Jaakkola International Conference on Machine Learning, 3419-3430, 2020 | 310 | 2020 |
| Deep-carving: Discovering visual attributes by carving deep neural nets S Shankar, VK Garg, R Cipolla Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 79 | 2015 |
| Link label prediction in signed social networks P Agrawal, VK Garg, R Narayanam Twenty-third international joint conference on artificial intelligence, 2013 | 73 | 2013 |
| Online optimization for the smart (micro) grid B Narayanaswamy, VK Garg, TS Jayram Proceedings of the 3rd international conference on future energy systems …, 2012 | 66 | 2012 |
| Multiresolution matrix factorization R Kondor, N Teneva, V Garg International Conference on Machine Learning, 1620-1628, 2014 | 62 | 2014 |
| Provably expressive temporal graph networks A Souza, D Mesquita, S Kaski, V Garg Advances in neural information processing systems 35, 32257-32269, 2022 | 53 | 2022 |
| Adaptivity to local smoothness and dimension in kernel regression S Kpotufe, V Garg Advances in neural information processing systems 26, 2013 | 52 | 2013 |
| Novel biobjective clustering (BiGC) based on cooperative game theory VK Garg, Y Narahari, MN Murty IEEE Transactions on Knowledge and Data Engineering 25 (5), 1070-1082, 2012 | 50 | 2012 |
| Supervising unsupervised learning V Garg, AT Kalai Advances in Neural Information Processing Systems 31, 2018 | 33 | 2018 |
| Learning tree structured potential games V Garg, T Jaakkola Advances in Neural Information Processing Systems 29, 2016 | 25 | 2016 |
| Learn to expect the unexpected: Probably approximately correct domain generalization V Garg, AT Kalai, K Ligett, S Wu International Conference on Artificial Intelligence and Statistics, 3574-3582, 2021 | 24 | 2021 |
| Solving graph compression via optimal transport V Garg, T Jaakkola Advances in Neural Information Processing Systems 32, 2019 | 21 | 2019 |
| Highly scalable parallel collaborative filtering algorithm A Narang, R Gupta, A Joshi, VK Garg 2010 International Conference on High Performance Computing, 1-10, 2010 | 18 | 2010 |
| Local aggregative games V Garg, T Jaakkola Advances in Neural Information Processing Systems 30, 2017 | 15 | 2017 |
| High throughput data redundancy removal algorithm with scalable performance S Bhattacherjee, A Narang, VK Garg Proceedings of the 6th International Conference on High Performance and …, 2011 | 15 | 2011 |
| Feature subspace SVMs (FS-SVMs) for high dimensional handwritten digit recognition VK Garg, MN Murty International Journal of Data Mining, Modelling and Management 1 (4), 411-436, 2009 | 15 | 2009 |
| Compositional sculpting of iterative generative processes T Garipov, S De Peuter, G Yang, V Garg, S Kaski, T Jaakkola Advances in neural information processing systems 36, 12665-12702, 2023 | 11 | 2023 |
| AbODE: Ab initio antibody design using conjoined ODEs Y Verma, M Heinonen, V Garg International Conference on Machine Learning, 35037-35050, 2023 | 10 | 2023 |
| Modular flows: Differential molecular generation Y Verma, S Kaski, M Heinonen, V Garg Advances in neural information processing systems 35, 12409-12421, 2022 | 10 | 2022 |
