| Deep end-to-end causal inference T Geffner, J Antoran, A Foster, W Gong, C Ma, E Kiciman, A Sharma, ... arXiv preprint arXiv:2202.02195, 2022 | 85 | 2022 |
| Compact policies for fully observable non-deterministic planning as SAT T Geffner, H Geffner Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018 | 52* | 2018 |
| Width-based planning for general video-game playing T Geffner, H Geffner Proceedings of the AAAI Conference on Artificial Intelligence and …, 2015 | 47 | 2015 |
| Using large ensembles of control variates for variational inference T Geffner, J Domke Advances in Neural Information Processing Systems 31, 2018 | 33 | 2018 |
| MCMC variational inference via uncorrected Hamiltonian annealing T Geffner, J Domke Advances in Neural Information Processing Systems 34, 639-651, 2021 | 29 | 2021 |
| Compositional score modeling for simulation-based inference T Geffner, G Papamakarios, A Mnih International Conference on Machine Learning, 11098-11116, 2023 | 25* | 2023 |
| On the difficulty of unbiased alpha divergence minimization T Geffner, J Domke arXiv preprint arXiv:2010.09541, 2020 | 21 | 2020 |
| Empirical evaluation of biased methods for alpha divergence minimization T Geffner, J Domke arXiv preprint arXiv:2105.06587, 2021 | 13 | 2021 |
| Approximation based variance reduction for reparameterization gradients T Geffner, J Domke Advances in Neural Information Processing Systems 33, 2397-2407, 2020 | 11 | 2020 |
| Langevin diffusion variational inference T Geffner, J Domke International Conference on Artificial Intelligence and Statistics, 576-593, 2023 | 8 | 2023 |
| Dual control variate for faster black-box variational inference X Wang, T Geffner, J Domke arXiv preprint arXiv:2210.07290, 2022 | 8* | 2022 |
| A Rule for Gradient Estimator Selection, with an Application to Variational Inference T Geffner, J Domke arXiv preprint arXiv:1911.01894, 2019 | 4 | 2019 |
| Variational inference with locally enhanced bounds for hierarchical models T Geffner, J Domke arXiv preprint arXiv:2203.04432, 2022 | 3 | 2022 |
| PINDER: The protein interaction dataset and evaluation resource D Kovtun, M Akdel, A Goncearenco, G Zhou, G Holt, D Baugher, D Lin, ... bioRxiv, 2024.07. 17.603980, 2024 | 2 | 2024 |
| Aligning target-aware molecule diffusion models with exact energy optimization S Gu, M Xu, A Powers, W Nie, T Geffner, K Kreis, J Leskovec, A Vahdat, ... arXiv preprint arXiv:2407.01648, 2024 | 2 | 2024 |
| Bending and Binding: Predicting Protein Flexibility upon Ligand Interaction using Diffusion Models X Zhang, T Geffner, M McPartlon, M Akdel, D Abramson, G Holt, ... NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | 2 | 2023 |
| Latentdock: Protein-protein docking with latent diffusion M McPartlon, C Marquet, T Geffner, D Kovtun, A Goncearenco, ... MLSB, 2023 | 1 | 2023 |
| Energy-Based Diffusion Language Models for Text Generation M Xu, T Geffner, K Kreis, W Nie, Y Xu, J Leskovec, S Ermon, A Vahdat arXiv preprint arXiv:2410.21357, 2024 | | 2024 |
| Truncated Consistency Models S Lee, Y Xu, T Geffner, G Fanti, K Kreis, A Vahdat, W Nie arXiv preprint arXiv:2410.14895, 2024 | | 2024 |
| Stochastic Flow Matching for Resolving Small-Scale Physics S Fotiadis, N Brenowitz, T Geffner, Y Cohen, M Pritchard, A Vahdat, ... arXiv preprint arXiv:2410.19814, 2024 | | 2024 |
