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Seungwook Han
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Equivariant contrastive learning
R Dangovski, L Jing, C Loh, S Han, A Srivastava, B Cheung, P Agrawal, ...
arXiv preprint arXiv:2111.00899, 2021
1122021
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
162024
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
142021
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
132023
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
102023
not-so-biggan: Generating highfidelity images on a small compute budget
S Han, A Srivastava, C Hurwitz, P Sattigeri, DD Cox
arXiv preprint arXiv:2009.04433 2, 2020
82020
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
52022
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
52019
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
42023
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
32023
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
22020
Value Augmented Sampling for Language Model Alignment and Personalization
S Han, I Shenfeld, A Srivastava, Y Kim, P Agrawal
arXiv preprint arXiv:2405.06639, 2024
12024
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
12023
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
Value Augmented Sampling: Predict Your Rewards To Align Language Models
S Han, I Shenfeld, A Srivastava, Y Kim, P Agrawal
ICLR 2024 Workshop on Reliable and Responsible Foundation Models, 0
On Assimilating Learned Views in Contrastive Learning
L Han, S Han, S Sudalairaj, C Loh, R Dangovski, P Agrawal, DN Metaxas, ...
Scaling Densities For Improved Density Ratio Estimation
A Srivastava, S Han, B Rhodes, K Xu, MU Gutmann
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