| How Good is the Bayes Posterior in Deep Neural Networks Really? F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ... International Conference on Machine Learning (ICML), 2020 | 383 | 2020 |
| Deepcoder: Semi-parametric variational autoencoders for automatic facial action coding DL Tran, R Walecki, O Rudovic, S Eleftheriadis, B Schuller, M Pantic Proceedings of the IEEE International Conference on Computer Vision, 3190-3199, 2017 | 72 | 2017 |
| GAGAN: Geometry-Aware Generative Adversarial Networks J Kossaifi, L Tran, Y Panagakis, M Pantic Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 66 | 2018 |
| The k-tied normal distribution: A compact parameterization of gaussian mean field posteriors in bayesian neural networks J Swiatkowski, K Roth, B Veeling, L Tran, J Dillon, J Snoek, S Mandt, ... International Conference on Machine Learning, 9289-9299, 2020 | 62 | 2020 |
| Joinable: Learning bottom-up assembly of parametric cad joints KDD Willis, PK Jayaraman, H Chu, Y Tian, Y Li, D Grandi, A Sanghi, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 61 | 2022 |
| Hydra: Preserving Ensemble Diversity for Model Distillation L Tran, BS Veeling, K Roth, J Swiatkowski, JV Dillon, J Snoek, S Mandt, ... ICML Workshop on Uncertainty & Robustness in Deep Learning, 2020 | 55 | 2020 |
| Masktune: Mitigating spurious correlations by forcing to explore S Asgari, A Khani, F Khani, A Gholami, L Tran, A Mahdavi Amiri, ... Advances in Neural Information Processing Systems 35, 23284-23296, 2022 | 29* | 2022 |
| Disentangling geometry and appearance with regularised geometry-aware generative adversarial networks L Tran, J Kossaifi, Y Panagakis, M Pantic International Journal of Computer Vision 127, 824-844, 2019 | 16 | 2019 |
| ProfPPIdb: pairs of physical protein-protein interactions predicted for entire proteomes L Tran, T Hamp, B Rost PLOS ONE, 2018 | 16 | 2018 |
| Generalizable Pose Estimation Using Implicit Scene Representations V Saxena, KR Malekshan, L Tran, Y Koga arXiv preprint arXiv:2305.17252, 2023 | 13 | 2023 |
| Cauchy-schwarz regularized autoencoder L Tran, M Pantic, MP Deisenroth The Journal of Machine Learning Research 23 (1), 5010-5046, 2022 | 13 | 2022 |
| COIL: Constrained optimization in learned latent space: learning representations for valid solutions PJ Bentley, SL Lim, A Gaier, L Tran Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 8 | 2022 |
| Evolving through the looking glass: Learning improved search spaces with variational autoencoders PJ Bentley, SL Lim, A Gaier, L Tran International Conference on Parallel Problem Solving from Nature, 371-384, 2022 | 7 | 2022 |
| SimCURL: Simple Contrastive User Representation Learning from Command Sequences H Chu, AH Khasahmadi, KDD Willis, F Anderson, Y Mao, L Tran, ... arXiv preprint arXiv:2207.14760, 2022 | 4 | 2022 |
| Group-disentangled Representation Learning with Weakly-Supervised Regularization L Tran, AH Khasahmadi, A Sanghi, S Asgari arXiv preprint arXiv:2110.12185, 2021 | 1 | 2021 |
| Representation Learning for Sequential Volumetric Design Tasks MF Alam, Y Wang, L Tran, CY Cheng, J Luo arXiv preprint arXiv:2309.02583, 2023 | | 2023 |
| Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness SA Taghanaki, A Gholami, F Khani, K Choi, L Tran, R Zhang, A Khani arXiv preprint arXiv:2207.01548, 2022 | | 2022 |
| Human-controllable and structured deep generative models DL Tran Imperial College London, 2022 | | 2022 |
| Weakly-supervised group disentanglement using total correlation L Tran, SA Taghanaki, AH Khasahmadi, A Sanghi Workshop on Weakly Supervised Learning (WeaSuL) at the International …, 2021 | | 2021 |
Tim SalimansGoogle DeepMind AmsterdamVerified email at google.com
