1 code implementation • 13 Mar 2024 • Asad Aali, Giannis Daras, Brett Levac, Sidharth Kumar, Alexandros G. Dimakis, Jonathan I. Tamir
We open-source our code and the trained Ambient Diffusion MRI models: https://github. com/utcsilab/ambient-diffusion-mri .
1 code implementation • NeurIPS 2023 • Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alexandros G. Dimakis, Sanjay Shakkottai
We present the first framework to solve linear inverse problems leveraging pre-trained latent diffusion models.
1 code implementation • NeurIPS 2023 • Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alexandros G. Dimakis, Adam Klivans
We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples.
1 code implementation • NeurIPS 2023 • Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms.
no code implementations • 6 Mar 2023 • Sitan Chen, Giannis Daras, Alexandros G. Dimakis
We develop a framework for non-asymptotic analysis of deterministic samplers used for diffusion generative modeling.
1 code implementation • 30 Nov 2022 • Giannis Daras, Alexandros G. Dimakis
We extend Textual Inversion to learn pseudo-words that represent a concept at different resolutions.
1 code implementation • 20 Oct 2022 • Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alexandros G. Dimakis
We find a surprising connection between multitask learning and robustness to neuron failures.
no code implementations • 12 Sep 2022 • Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G. Dimakis, Peyman Milanfar
To reverse these general diffusions, we propose a new objective called Soft Score Matching that provably learns the score function for any linear corruption process and yields state of the art results for CelebA.
Ranked #7 on Image Generation on CelebA 64x64
2 code implementations • 18 Jun 2022 • Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis
In practice, to allow for increased expressivity, we propose to do posterior sampling in the latent space of a pre-trained generative model.
no code implementations • 1 Jun 2022 • Giannis Daras, Alexandros G. Dimakis
We discover that DALLE-2 seems to have a hidden vocabulary that can be used to generate images with absurd prompts.
no code implementations • 16 Dec 2021 • Giannis Daras, Wen-Sheng Chu, Abhishek Kumar, Dmitry Lagun, Alexandros G. Dimakis
We introduce a novel framework for solving inverse problems using NeRF-style generative models.
no code implementations • NeurIPS Workshop Deep_Invers 2021 • Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alex Dimakis, Jonathan Tamir
The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep generative priors can be powerful tools for solving inverse problems.
2 code implementations • NeurIPS 2021 • Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir
The CSGM framework (Bora-Jalal-Price-Dimakis'17) has shown that deep generative priors can be powerful tools for solving inverse problems.
2 code implementations • 15 Feb 2021 • Giannis Daras, Joseph Dean, Ajil Jalal, Alexandros G. Dimakis
We propose Intermediate Layer Optimization (ILO), a novel optimization algorithm for solving inverse problems with deep generative models.
1 code implementation • NeurIPS 2020 • Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis
We propose a novel type of balanced clustering algorithm to approximate attention.
1 code implementation • 11 Oct 2020 • Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis
We also show that SMYRF can be used interchangeably with dense attention before and after training.
2 code implementations • CVPR 2020 • Giannis Daras, Augustus Odena, Han Zhang, Alexandros G. Dimakis
We introduce a new local sparse attention layer that preserves two-dimensional geometry and locality.
Ranked #19 on Conditional Image Generation on ImageNet 128x128