Alexandros Graikos

I am a PhD student at Stony Brook University, advised by Dimitris Samaras. My research interests revolve around the rich image priors encoded in deep generative models. More details about our work on learning and using such priors for the digital histopathology and satellite image domains here.

I also interned at Microsoft Research where with my mentor Nebojsa Jojic we worked on interesting diffusion model prior problems.

Email / GitHub / Google Scholar / CV
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Selected Research

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Fast constrained sampling in pre-trained diffusion models

Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras

NeurIPS, 2025

We speed up training-free inference in diffusion models using an approximation to Newton's method. This is the algorithm that powers ZoomLDM. We also made a short game that uses this algorithm to generate diffusion images in real-time [Gameplay 1 / Gameplay 2].

Code / arXiv
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PixCell: A generative foundation model for digital histopathology images

Alexandros Graikos*, S. Yellapragada*, Z. Li, K. Triaridis, V. Belagali, T. N. Nandi, K. Bai, B. S. Knudsen, T. Kurc, R. R. Gupta, P. Prasanna, R. K Madduri, J. Saltz, Dimitris Samaras

Preprint

The first generative foundation model for digital histopathology images. We demonstrate the ability to preserve privacy by utilizing synthetic data, and solve generative tasks such as virtual staining.

PixCell-1024 🤗 / PixCell-256 🤗 / arXiv
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ZoomLDM: Latent Diffusion Model for multi-scale image generation

Alexandros Graikos*, Srikar Yellapragada*, Kostas Triaridis, Prateek Prasanna, Rajarsi R. Gupta, Joel Saltz, Dimitris Samaras

CVPR, 2025

We propose a multi-scale diffusion model to make generation of massive pathology images feasible.

Code / arXiv / Large Image Viewer
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Learned representation-guided diffusion models for large-image generation

Alexandros Graikos*, Srikar Yellapragada*, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel Saltz, Dimitris Samaras

CVPR, 2024

We use self-supervised models to provide annotations for diffusion models in digital pathology. Exploiting the unique structure of the data, we synthesize large images with only a patch-based model.

Code / arXiv
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Conditional Generation from Unconditional Diffusion Models using Denoiser Representations

Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras

BMVC, 2023

We show that we can learn to control generation with as few as 20 examples using the existing denoiser representations.

Code / arXiv
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Diffusion models as plug-and-play priors

Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras

NeurIPS 2022

Diffusion models can be used in inference tasks without any additional training. You can even solve the traveling salesman problem with a diffusion model (left).

Code / arXiv
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Single-Image Based Food Volume Estimation

Alexandros Graikos, Vasileios Charisis, Dimitrios Iakovakis, Stelios Hadjidimitriou, Leontios Hadjileontiadis

HCI International 2020

Training and applying monocular depth estimation models to estimate the food volume from a given RGB image.

Code / Paper
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Monocular Depth Estimation using Generative Adversarial Networks

Alexandros Graikos, Anastasios Delopoulos

Undergraduate Thesis, 2018

Adding GAN losses to monocular depth estimation models improves predicted depth accuracy.

Code

Papers

2026

Generating metamers of human scene understanding

Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn, Dimitris Samaras, Greg Zelinsky
ICLR, 2026

2025

Fast constrained sampling in pre-trained diffusion models

Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras
NeurIPS, 2025

PixCell: A generative foundation model for digital histopathology images

Alexandros Graikos*, S. Yellapragada*, Z. Li, K. Triaridis, V. Belagali, T. N. Nandi, K. Bai, B. S. Knudsen, T. Kurc, R. R. Gupta, P. Prasanna, R. K Madduri, J. Saltz, Dimitris Samaras
Preprint

Pathology Image Compression with Pre-trained Autoencoders

Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis, Zilinghan Li, Tarak Nath Nandi, Ravi K Madduri, Prateek Prasanna, Joel Saltz, Dimitris Samaras
MICCAI, 2025

PathSegDiff: Pathology Segmentation using Diffusion model representations

Sachin Kumar Danisetty, Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras
5th Deep Generative Models Workshop @ MICCAI 2025

Seen2Scene: a generative model of fixation-by-fixation scene understanding

Ritik Raina, Abe Leite, Alexandros Graikos, Seoyoung Ahn, Greg Zelinsky
CCN, 2025

ZoomLDM: Latent Diffusion Model for multi-scale image generation

Alexandros Graikos*, Srikar Yellapragada*, Kostas Triaridis, Prateek Prasanna, Rajarsi R. Gupta, Joel Saltz, Dimitris Samaras
CVPR, 2025

2024

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning

Varun Belagali*, Srikar Yellapragada*, Alexandros Graikos, Saarthak Kapse, Zilinghan Li, Tarak Nath Nandi, Ravi K Madduri, Prateek Prasanna, Joel Saltz, Dimitris Samaras
Preprint

∞-Brush: Controllable Large Image Synthesis with Diffusion Models in Infinite Dimensions

Minh-Quan Le*, Alexandros Graikos*, Srikar Yellapragada, Rajarsi Gupta, Joel Saltz, Dimitris Samaras
ECCV, 2024

Diffusion-Refined VQA Annotations for Semi-Supervised Gaze Following

Qiaomu Miao, Alexandros Graikos, Jingwei Zhang, Sounak Mondal, Minh Hoai, Dimitris Samaras
ECCV, 2024

Learned representation-guided diffusion models for large-image generation

Alexandros Graikos*, Srikar Yellapragada*, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel Saltz, Dimitris Samaras
CVPR, 2024

PathLDM: Text conditioned Latent Diffusion Model for Histopathology

Srikar Yellapragada*, Alexandros Graikos*, Prateek Prasanna, Tahsin Kurc, Joel Saltz, Dimitris Samaras
WACV, 2024

2023

Conditional Generation from Unconditional Diffusion Models using Denoiser Representations

Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras
BMVC, 2023

S-volsdf: Sparse multi-view stereo regularization of neural implicit surfaces

Haoyu Wu, Alexandros Graikos, Dimitris Samaras
ICCV, 2023

GFlowNet-EM for learning compositional latent variable models

Edward Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio
ICML, 2023

2022

Diffusion models as plug-and-play priors

Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras
NeurIPS, 2022

Resolving label uncertainty with implicit generative models

Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic
UAI, 2022

2020

Single-Image Based Food Volume Estimation

Alexandros Graikos, Vasileios Charisis, Dimitrios Iakovakis, Stelios Hadjidimitriou, Leontios Hadjileontiadis
HCI International, 2020