| DataComp: In search of the next generation of multimodal datasets SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ... Advances in Neural Information Processing Systems (NeurIPS 2023) 36, 2023 | 361 | 2023 |
| Robust compressed sensing mri with deep generative priors A Jalal, M Arvinte, G Daras, E Price, AG Dimakis, J Tamir Advances in Neural Information Processing Systems (NeurIPS 2021) 34, 14938-14954, 2021 | 314 | 2021 |
| Soft diffusion: Score matching for general corruptions G Daras, M Delbracio, H Talebi, AG Dimakis, P Milanfar TMLR 2023, 2022 | 106 | 2022 |
| Intermediate layer optimization for inverse problems using deep generative models G Daras, J Dean, A Jalal, AG Dimakis International Conference on Machine Learning (ICML), 2021 | 98 | 2021 |
| Your local GAN: Designing two dimensional local attention mechanisms for generative models G Daras, A Odena, H Zhang, AG Dimakis Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 81 | 2020 |
| Discovering the hidden vocabulary of dalle-2 G Daras, AG Dimakis Score-Based Modeling Workshop @ NeurIPS 2022, 2022 | 80 | 2022 |
| Restoration-degradation beyond linear diffusions: A non-asymptotic analysis for ddim-type samplers S Chen, G Daras, A Dimakis International Conference on Machine Learning, 4462-4484, 2023 | 73 | 2023 |
| Datacomp-lm: In search of the next generation of training sets for language models J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, S Gadre, H Bansal, E Guha, ... arXiv preprint arXiv:2406.11794, 2024 | 70* | 2024 |
| Solving linear inverse problems provably via posterior sampling with latent diffusion models L Rout, N Raoof, G Daras, C Caramanis, AG Dimakis, S Shakkottai Advances in Neural Information Processing Systems (NeurIPS 2023) 36, 2023 | 64 | 2023 |
| Ambient Diffusion: Learning Clean Distributions from Corrupted Data G Daras, K Shah, Y Dagan, A Gollakota, AG Dimakis, A Klivans Advances in Neural Information Processing Systems (NeurIPS 2023) 36, 2023 | 47 | 2023 |
| Smyrf: Efficient attention using asymmetric clustering G Daras, N Kitaev, A Odena, AG Dimakis Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020 | 46 | 2020 |
| Consistent diffusion models: Mitigating sampling drift by learning to be consistent G Daras, Y Dagan, AG Dimakis, C Daskalakis Advances in Neural Information Processing Systems (NeurIPS 2023) 36, 2023 | 39 | 2023 |
| Multiresolution Textual Inversion G Daras, AG Dimakis Score-Based Modeling Workshop @ NeurIPS 2022, 2022 | 31 | 2022 |
| Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems G Daras, Y Dagan, AG Dimakis, C Daskalakis International Conference on Machine Learning (ICML), 2022 | 21 | 2022 |
| Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data G Daras, AG Dimakis, C Daskalakis International Conference on Machine Learning (ICML) 2024, 2024 | 13 | 2024 |
| A survey on diffusion models for inverse problems G Daras, H Chung, CH Lai, Y Mitsufuji, JC Ye, P Milanfar, AG Dimakis, ... arXiv preprint arXiv:2410.00083, 2024 | 9 | 2024 |
| Solving inverse problems with nerfgans G Daras, WS Chu, A Kumar, D Lagun, AG Dimakis arXiv preprint arXiv:2112.09061, 2021 | 8 | 2021 |
| Single-shot adaptation using score-based models for mri reconstruction M Arvinte, A Jalal, G Daras, E Price, A Dimakis, JI Tamir International Society for Magnetic Resonance in Medicine, Annual Meeting 42, 2022 | 7 | 2022 |
| Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data A Aali, G Daras, B Levac, S Kumar, AG Dimakis, JI Tamir International Conference on Learning Representations (ICLR) 2025, 2024 | 4 | 2024 |
| Solving Inverse Problems with Ambient Diffusion G Daras, A Dimakis NeurIPS 2023 Workshop on Deep Learning and Inverse Problems, 2023 | 4 | 2023 |
Alexandros G DimakisProfessor, ECE University of Texas at AustinPotvrđena adresa e-pošte na austin.utexas.edu