Nevae: A deep generative model for molecular graphs B Samanta, A De, G Jana, V Gómez, PK Chattaraj, N Ganguly, ... The Journal of Machine Learning Research 21 (1), 4556-4588, 2020 | 213 | 2020 |
Enhancing human learning via spaced repetition optimization B Tabibian, U Upadhyay, A De, A Zarezade, B Schölkopf, ... Proceedings of the National Academy of Sciences 116 (10), 3988-3993, 2019 | 194 | 2019 |
Grad-match: Gradient matching based data subset selection for efficient deep model training K Killamsetty, S Durga, G Ramakrishnan, A De, R Iyer International Conference on Machine Learning, 5464-5474, 2021 | 167 | 2021 |
Learning and forecasting opinion dynamics in social networks A De, I Valera, N Ganguly, S Bhattacharya, M Gomez Rodriguez Advances in neural information processing systems 29, 2016 | 131* | 2016 |
Deep reinforcement learning of marked temporal point processes U Upadhyay, A De, M Gomez Rodriguez Advances in neural information processing systems 31, 2018 | 122 | 2018 |
Learning a linear influence model from transient opinion dynamics A De, S Bhattacharya, P Bhattacharya, N Ganguly, S Chakrabarti Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 87* | 2014 |
Regression under human assistance A De, P Koley, N Ganguly, M Gomez-Rodriguez Proceedings of the AAAI Conference on Artificial Intelligence 34 (03), 2611-2620, 2020 | 68 | 2020 |
Knowlywood: Mining activity knowledge from hollywood narratives N Tandon, G De Melo, A De, G Weikum Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 64 | 2015 |
Designing random graph models using variational autoencoders with applications to chemical design B Samanta, A De, N Ganguly, M Gomez-Rodriguez arXiv preprint arXiv:1802.05283, 2018 | 55 | 2018 |
Differentiable learning under triage N Okati, A De, M Rodriguez Advances in Neural Information Processing Systems 34, 9140-9151, 2021 | 53 | 2021 |
Classification under human assistance A De, N Okati, A Zarezade, MG Rodriguez Proceedings of the AAAI Conference on Artificial Intelligence 35 (7), 5905-5913, 2021 | 51 | 2021 |
Discriminative link prediction using local, community, and global signals A De, S Bhattacharya, S Sarkar, N Ganguly, S Chakrabarti IEEE Transactions on Knowledge and Data Engineering 28 (8), 2057-2070, 2016 | 42 | 2016 |
Counterfactual explanations in sequential decision making under uncertainty S Tsirtsis, A De, M Rodriguez Advances in Neural Information Processing Systems 34, 30127-30139, 2021 | 41 | 2021 |
Learning temporal point processes with intermittent observations V Gupta, S Bedathur, S Bhattacharya, A De International Conference on Artificial Intelligence and Statistics, 3790-3798, 2021 | 29* | 2021 |
Steering Social Activity: A Stochastic Optimal Control Point Of View. A Zarezade, A De, U Upadhyay, HR Rabiee, M Gomez-Rodriguez Journal of Machine Learning Research 18, 205:1-205:35, 2017 | 29 | 2017 |
Interpretable neural subgraph matching for graph retrieval I Roy, VSBR Velugoti, S Chakrabarti, A De Proceedings of the AAAI conference on artificial intelligence 36 (7), 8115-8123, 2022 | 24 | 2022 |
Training data subset selection for regression with controlled generalization error S Durga, R Iyer, G Ramakrishnan, A De International Conference on Machine Learning, 9202-9212, 2021 | 23 | 2021 |
Learning to switch between machines and humans VB Meresht, A De, A Singla, M Gomez-Rodriguez arXiv preprint arXiv:2002.04258, 2020 | 22 | 2020 |
Demarcating endogenous and exogenous opinion dynamics: An experimental design approach P Koley, A Saha, S Bhattacharya, N Ganguly, A De ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (6), 1-25, 2021 | 21* | 2021 |
LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity. B Samanta, A De, A Chakraborty, N Ganguly IJCAI, 2679-2685, 2017 | 21 | 2017 |