2 citations · 4 across the 16 of their papers we have counts for
21 papers
BigCell: Generating Gigapixel Whole-Slide Images
Srikar Yellapragada, Alexandros Graikos, Zilinghan Li +10
Whole-slide images (WSIs) are gigapixel-scale digital scans of histopathology tissue and serve as the primary basis for cancer diagnosis. Existing histopathology generative models…
Scaling Multi-Teacher Distillation for Digital Pathology
Sofiène Boutaj, Pierre Marza, Varun Belagali +3
Multi-teacher distillation allows transferring knowledge from multiple "teacher" networks to a single "student" network. This method is promising in fields such as digital patholog…
On the spectral properties of generative denoiser Jacobians
Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras
Generative denoising models, such as diffusion and flow-matching, learn to sample from complex distributions by training a deep neural network denoiser to recover clean data from n…
A General-Purpose VLM Can Teach an Astronomy Foundation Model to Better Recognize Galaxy Morphology
Dichang Zhang, Jiaqi Deng, Yixuan Shao +7
Existing astronomy foundation models provide strong galaxy representations, but adapting them to new survey conditions and survey-specific morphology recognition tasks still requir…
Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes
Minh-Quan Le, Armand Comas, Alexandros Lattas +7
Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws , each modality reshapes the other. In this paper, we…
Poppy: Polarization-based Plug-and-Play Guidance for Enhancing Monocular Normal Estimation
Irene Kim, Sai Tanmay Reddy Chakkera, Alexandros Graikos +2
Monocular surface normal estimators trained on large-scale RGB-normal data often perform poorly in the edge cases of reflective, textureless, and dark surfaces. Polarization encode…
AS-Bridge: A Bidirectional Generative Framework Bridging Next-Generation Astronomical Surveys
Dichang Zhang, Yixuan Shao, Simon Birrer +1
The upcoming decade of observational cosmology will be shaped by large sky surveys, such as the ground-based LSST at the Vera C. Rubin Observatory and the space-based Euclid missio…
Generating metamers of human scene understanding
Ritik Raina, Abe Leite, Alexandros Graikos +3
Human vision combines low-resolution "gist" information from the visual periphery with sparse but high-resolution information from fixated locations to construct a coherent underst…
TICON: A Slide-Level Tile Contextualizer for Histopathology Representation Learning
Varun Belagali, Saarthak Kapse, Pierre Marza +12
The interpretation of small tiles in large whole slide images (WSI) often needs a larger image context. We introduce TICON, a transformer-based tile representation contextualizer t…
GriDiT: Factorized Grid-Based Diffusion for Efficient Long Image Sequence Generation
Snehal Singh Tomar, Alexandros Graikos, Arjun Krishna +2
Modern deep learning methods typically treat image sequences as large tensors of sequentially stacked frames. However, is this straightforward representation ideal given the curren…
CDG-MAE: Cross-view Masked Modeling using Diffusion Generated Views
Varun Belagali, Pierre Marza, Srikar Yellapragada +7
Cross-view masked autoencoding has emerged as a powerful pretext task for learning dense correspondences, which are essential for applications such as video label propagation. The…
PixCell: A generative foundation model for digital histopathology images
Srikar Yellapragada, Alexandros Graikos, Zilinghan Li +11
The digitization of histology slides has revolutionized pathology, providing massive datasets for cancer diagnosis and research. Self-supervised and vision-language models have bee…
PathSegDiff: Pathology Segmentation using Diffusion model representations
Sachin Kumar Danisetty, Alexandros Graikos, Srikar Yellapragada +1
Image segmentation is crucial in many computational pathology pipelines, including accurate disease diagnosis, subtyping, outcome, and survivability prediction. The common approach…
Pathology Image Compression with Pre-trained Autoencoders
Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis +6
The growing volume of high-resolution Whole Slide Images in digital histopathology poses significant storage, transmission, and computational efficiency challenges. Standard compre…
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment
Minh-Quan Le, Gaurav Mittal, Tianjian Meng +5
While diffusion models are powerful in generating high-quality, diverse synthetic data for object-centric tasks, existing methods struggle with scene-aware tasks such as Visual Que…
Leveraging Registers in Vision Transformers for Robust Adaptation
Srikar Yellapragada, Kowshik Thopalli, Vivek Narayanaswamy +5
Vision Transformers (ViTs) have shown success across a variety of tasks due to their ability to capture global image representations. Recent studies have identified the existence o…
Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning
Varun Belagali, Srikar Yellapragada, Alexandros Graikos +7
Self-supervised learning (SSL) methods have emerged as strong visual representation learners by training an image encoder to maximize similarity between features of different views…
ZoomLDM: Latent Diffusion Model for multi-scale image generation
Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis +4
Diffusion models have revolutionized image generation, yet several challenges restrict their application to large-image domains, such as digital pathology and satellite imagery. Gi…
Fast constrained sampling in pre-trained diffusion models
Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras
Large denoising diffusion models, such as Stable Diffusion, have been trained on billions of image-caption pairs to perform text-conditioned image generation. As a byproduct of thi…
-Brush: Controllable Large Image Synthesis with Diffusion Models in Infinite Dimensions
Minh-Quan Le, Alexandros Graikos, Srikar Yellapragada +3
Synthesizing high-resolution images from intricate, domain-specific information remains a significant challenge in generative modeling, particularly for applications in large-image…
Diffusion-Refined VQA Annotations for Semi-Supervised Gaze Following
Qiaomu Miao, Alexandros Graikos, Jingwei Zhang +3
Training gaze following models requires a large number of images with gaze target coordinates annotated by human annotators, which is a laborious and inherently ambiguous process.…