| Equivariant contrastive learning R Dangovski, L Jing, C Loh, S Han, A Srivastava, B Cheung, P Agrawal, ... arXiv preprint arXiv:2111.00899, 2021 | 104 | 2021 |
| Gage MPC: bypassing residual function leakage for non-interactive MPC G Almashaqbeh, F Benhamouda, S Han, D Jaroslawicz, T Malkin, A Nicita, ... Cryptology ePrint Archive, 2021 | 13 | 2021 |
| Compositional foundation models for hierarchical planning A Ajay, S Han, Y Du, S Li, A Gupta, T Jaakkola, J Tenenbaum, L Kaelbling, ... Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Yilun Du, Shaung Li, Abhi Gupta, Tommi Jaakkola, Josh Tenenbaum, Leslie Kaelbling, Akash Srivastava, and Pulkit Agrawal. Compositional foundation models for hierarchical planning A Ajay, S Han arXiv preprint arXiv:2309.08587 3, 2023 | 10 | 2023 |
| Estimating the density ratio between distributions with high discrepancy using multinomial logistic regression A Srivastava, S Han, K Xu, B Rhodes, MU Gutmann arXiv preprint arXiv:2305.00869, 2023 | 7 | 2023 |
| not-so-biggan: Generating high-fidelity images on a small compute budget S Han, A Srivastava, C Hurwitz, P Sattigeri, DD Cox arXiv preprint arXiv:2009.04433 2, 2020 | 6 | 2020 |
| Constructive assimilation: Boosting contrastive learning performance through view generation strategies L Han, S Han, S Sudalairaj, C Loh, R Dangovski, F Deng, P Agrawal, ... arXiv preprint arXiv:2304.00601, 2023 | 4 | 2023 |
| Predicting the accuracy of neural networks from final and intermediate layer outputs C DeChant, S Han, H Lipson ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena, 2019 | 4 | 2019 |
| Multi-symmetry ensembles: Improving diversity and generalization via opposing symmetries C Loh, S Han, S Sudalairaj, R Dangovski, K Xu, F Wenzel, M Soljacic, ... International Conference on Machine Learning, 22614-22630, 2023 | 3 | 2023 |
| On the Importance of Calibration in Semi-supervised Learning C Loh, R Dangovski, S Sudalairaj, S Han, L Han, L Karlinsky, M Soljacic, ... arXiv preprint arXiv:2210.04783, 2022 | 2 | 2022 |
| 3D distributed deep learning framework for prediction of human intelligence from brain MRI S Han, Y Zhang, Y Ren, J Posner, S Yoo, J Cha Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and …, 2020 | 2 | 2020 |
| Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging C Loh, R Dangovski, S Sudalairaj, S Han, L Han, L Karlinsky, M Soljacic, ... Transactions on Machine Learning Research, 2023 | 1 | 2023 |
| Training a Large-Scale 3D Convolutional Neural Network Predicting Human Intelligence in Adolescent Brain Cognitive Development Study S Han, Y Zhang, Y Ren, S Yoo, J Cha | | 2022 |
| On Assimilating Learned Views in Contrastive Learning L Han, S Han, S Sudalairaj, C Loh, R Dangovski, P Agrawal, DN Metaxas, ... | | 2022 |
| Scaling Densities For Improved Density Ratio Estimation A Srivastava, S Han, B Rhodes, K Xu, MU Gutmann | | 2021 |
Akash SrivastavaMIT, IBM Research, University of EdinburghVerified email at mit.edu
