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Ambient Diffusion: Reducing Dataset Memorization by Training with Heavily Corrupted Data

5 minute read

Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models

Published in CVPR 2020 [Paper] [Code]

Citation: Giannis Daras, Augustus Odena, Han Zhang, Alexandros G. Dimakis, "Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models", CVPR 2020

SMYRF: Efficient Attention using Asymmetric Clustering

Published in NeurIPS 2020 [Paper] [Code]

Citation: Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis, "SMYRF: Efficient Attention using Asymmetric Clustering", NeurIPS 2020

Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

Published in ICML 2021 [Paper] [Code]

Citation: Giannis Daras , Joseph Dean, Ajil Jalal, Alexandros G. Dimakis, "Intermediate Layer Optimization for Inverse Problems using Deep Generative Models", ICML 2021

Robust Compressed Sensing MRI with Deep Generative Priors

Published in NeurIPS 2021 [Paper] [Code]

Citation: Ajil Jalal, Marius Arvinte, Giannis Daras , Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir, "Robust Compressed Sensing MRI with Deep Generative Priors", NeurIPS 2021

Solving Inverse Problems with NerfGANs

Preprint [Paper]

Citation: Giannis Daras, Wen-Sheng Chu, Abhishek Kumar, Dmitry Lagun, Alexandros G. Dimakis, "Solving Inverse Problems with NerfGANs"

Discovering the Hidden Vocabulary of DALLE-2

Published in NeurIPS 2022 Workshop on Score-Based Methods [Paper]

Citation: Giannis Daras (*) , Alexandros G. Dimakis, "Discovering the Hidden Vocabulary of DALLE-2", NeurIPS 2022 Workshop on Score-Based Methods

Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve

Published in NeurIPS 2022 [Paper] [Code]

Citation: Giannis Daras (*) , Negin Raoof (*), Zoi Gkalitsiou, Alexandros G. Dimakis, "Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve", NeurIPS 2022

Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems

Published in ICML 2022 [Paper] [Code]

Citation: Giannis Daras (*) , Yuval Dagan (*), Alexandros G. Dimakis, Constantinos Daskalakis, "Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems", ICML 2022

Soft Diffusion: Score Matching for General Corruptions

Published in TMLR 2023 [Paper]

Citation: Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G. Dimakis, Peyman Milanfar, "Soft Diffusion: Score Matching for General Corruptions", TMLR 2023

Multiresolution Textual Inversion

Published as an Oral in NeurIPS 2022, SBM Workshop [Paper] [Code]

Citation: Giannis Daras, Alexandros G. Dimakis, "Multiresolution Textual Inversion", NeurIPS 2022, SBM Workshop

Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent

Published in NeurIPS 2023 [Paper] [Code]

Citation: Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis, "Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent", NeurIPS 2023

Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis for DDIM-Type Samplers

Published in ICML 2023 [Paper]

Citation: Sitan Chen, Giannis Daras, Alexandros G. Dimakis, "Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis for DDIM-Type Samplers", ICML 2023

DataComp: In search of the next generation of multimodal datasets

Published as an Oral in NeurIPS 2023 [Paper] [Code]

Citation: 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, "DataComp: In search of the next generation of multimodal datasets", NeurIPS 2023

Ambient Diffusion: Learning Clean Distributions from Corrupted Data

Published in NeurIPS 2023 [Paper] [Code]

Citation: Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alexandros G. Dimakis, Adam Klivans, "Ambient Diffusion: Learning Clean Distributions from Corrupted Data", NeurIPS 2023

Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models

Published in NeurIPS 2023 [Paper] [Code]

Citation: Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alexandros G. Dimakis, Sanjay Shakkottai, "Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models", NeurIPS 2023

Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

Published in ICML 2024 [Paper] [Code]

Citation: Giannis Daras, Alexandros G. Dimakis, Constantinos Daskalakis, "Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data", ICML 2024

DataComp-LM: In search of the next generation of training sets for language models

Published in NeurIPS 2024 Track Datasets and Benchmarks [Paper] [Code]

Citation: Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar, "DataComp-LM: In search of the next generation of training sets for language models", NeurIPS 2024 Track Datasets and Benchmarks

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data

Published in ICLR 2025 [Paper] [Code]

Citation: Asad Aali, Giannis Daras, Brett Levac, Sidharth Kumar, Alexandros G. Dimakis, Jonathan I. Tamir', "Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data", ICLR 2025

Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models

Published in ICLR 2025 [Paper]

Citation: Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alexandros G. Dimakis, "Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models", ICLR 2025

How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion

Published in ICLR 2025 [Paper] [Code]

Citation: Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis, "How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion", ICLR 2025

Ambient Diffusion Omni: Training Good Models with Bad Data

Published as an Spotlight in NeurIPS 2025 [Paper] [Code]

Citation: Giannis Daras*, Adrian Rodriguez-Munoz*, Adam Klivans, Antonio Torralba, Constantinos Daskalakis, "Ambient Diffusion Omni: Training Good Models with Bad Data", NeurIPS 2025

Ambient Proteins: Training Diffusion Models on Low Quality Structures

Published as an Spotlight in NeurIPS 2025 [Paper] [Code]

Citation: Giannis Daras*, Jeffrey Ouyang-Zhang*, Krithika Ravishankar, William Daspit, Costis Daskalakis, Qiang Liu, Adam Klivans, Daniel J. Diaz, "Ambient Proteins: Training Diffusion Models on Low Quality Structures", NeurIPS 2025

Google Summer of Code presentation - Athens Floss Meetup

Presented Google Summer of Code 2018 work for the project: “Adding Greek Language to spaCy” under the GFOSS — the Open Technologies Alliance.

Athens Crossroad: Machine Learning and Healthcare

In this talk, the latest advancements regarding the application of Artificial Intelligence on the field of Medicine are discussed at a roundtable session for the Athens Crossroad (12th Congress of the Hellenic Society of Thoracic & Cardiovascular Surgeons) conference, under the theme “Artificial Intelligence”. Use cases of Natural Language Processing algorithms, Brain Computer Interfaces and Deep Learning Architectures for Image Processing are outlined.

Improving sparse transformer models for efficient self-attention

One disadvantage of using attention layers in a neural network architecture is that the memory and time complexity of the operation is quadratic. This talk tries to address the following question: “Can we design attention layers with lower complexity that are able to discover all dependencies in the input?”. The answer seems to be yes, by modeling the problem of introducing sparsity to the attention layer with Information Flow Graphs.