| Identifiability of deep generative models without auxiliary information B Kivva, G Rajendran, P Ravikumar, B Aragam Advances in Neural Information Processing Systems 35, 15687-15701, 2022 | 50* | 2022 |
| Sum-of-squares lower bounds for sherrington-kirkpatrick via planted affine planes M Ghosh, FG Jeronimo, C Jones, A Potechin, G Rajendran 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS …, 2020 | 47 | 2020 |
| Learning latent causal graphs via mixture oracles B Kivva, G Rajendran, P Ravikumar, B Aragam Advances in Neural Information Processing Systems 34, 18087-18101, 2021 | 42 | 2021 |
| Learning linear causal representations from interventions under general nonlinear mixing S Buchholz, G Rajendran, E Rosenfeld, B Aragam, B Schölkopf, ... Advances in Neural Information Processing Systems 36, 2024 | 26 | 2024 |
| Sum-of-squares lower bounds for sparse independent set C Jones, A Potechin, G Rajendran, M Tulsiani, J Xu 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 23 | 2022 |
| Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families G Rajendran, B Kivva, M Gao, B Aragam Advances in Neural Information Processing Systems 34, 18660-18672, 2021 | 18 | 2021 |
| Machinery for proving sum-of-squares lower bounds on certification problems A Potechin, G Rajendran arXiv preprint arXiv:2011.04253, 2020 | 12 | 2020 |
| Concentration of polynomial random matrices via Efron-Stein inequalities G Rajendran, M Tulsiani Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023 | 9 | 2023 |
| Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis A Potechin, G Rajendran Advances in Neural Information Processing Systems 35, 35724-35740, 2022 | 9 | 2022 |
| Sum-of-squares lower bounds for densest k-subgraph C Jones, A Potechin, G Rajendran, J Xu Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 84-95, 2023 | 6 | 2023 |
| Analyzing robustness of end-to-end neural models for automatic speech recognition G Rajendran, W Zou arXiv preprint arXiv:2208.08509, 2022 | 4 | 2022 |
| Combinatorial optimization via the sum of squares hierarchy G Rajendran arXiv preprint arXiv:2208.04374, 2022 | 4 | 2022 |
| An interventional perspective on identifiability in gaussian lti systems with independent component analysis G Rajendran, P Reizinger, W Brendel, PK Ravikumar Causal Learning and Reasoning, 41-70, 2024 | 3 | 2024 |
| Nonlinear Random Matrices and Applications to the Sum of Squares Hierarchy G Rajendran The University of Chicago, 2022 | 3 | 2022 |
| Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models G Rajendran, S Buchholz, B Aragam, B Schölkopf, P Ravikumar arXiv preprint arXiv:2402.09236, 2024 | 1 | 2024 |
| On the Origins of Linear Representations in Large Language Models Y Jiang, G Rajendran, P Ravikumar, B Aragam, V Veitch arXiv preprint arXiv:2403.03867, 2024 | | 2024 |
