Noise2Stack: Improving Image Restoration by Learning from Volumetric Data. - Mikhail Papkov; Kenny Roberts; Lee Ann Madissoon; Ömer Bayraktar; Dmytro Fishman; Kaupo Palo; Leopold Parts (CoRR, 2020)

Noise2Stack: Improving Image Restoration by Learning from Volumetric Data. - Mikhail Papkov; Kenny Roberts; Lee Ann Madissoon; Jarrod Shilts; Ömer Bayraktar; Dmytro Fishman; Kaupo Palo; Leopold Parts (MLMIR@MICCAI, 2021)

Fast Fourier Convolutions in Self-Supervised Neural Networks for Image Denoising. - Joonas Ariva; Mikhail Papkov (Tiny Papers @ ICLR, 2023)

Self-Supervised Image Denoising with Swin Transformer. - Pavel Chizhov; Mikhail Papkov (Tiny Papers @ ICLR, 2023)

Reducing the Effect of Incomplete Annotations in Object Detection for Histopathology. - Denys Kaliuzhnyi; Dmytro Fishman; Mikhail Papkov (Tiny Papers @ ICLR, 2023)

Self-supervised Single-Image Deconvolution with Siamese Neural Networks. - Mikhail Papkov; Kaupo Palo; Leopold Parts (DALI@MICCAI, 2023)

Metadata Improves Segmentation Through Multitasking Elicitation. - Iaroslav Plutenko; Mikhail Papkov; Kaupo Palo; Leopold Parts; Dmytro Fishman (DART@MICCAI, 2023)

SwinIA: Self-Supervised Blind-Spot Image Denoising with Zero Convolutions. - Mikhail Papkov; Pavel Chizhov (CoRR, 2023)

Plots Unlock Time-Series Understanding in Multimodal Models. - Mayank Daswani; Mathias M. J. Bellaiche; Marc Wilson; Desislav Ivanov; Mikhail Papkov; Eva Schnider; Jing Tang; Kay Lamerigts; Gabriela Botea; Michael A. Sanchez; Yojan Patel; Shruthi Prabhakara; et al. (CoRR, 2024)

SwinIA: Self-Supervised Blind-Spot Image Denoising Without Convolutions. - Mikhail Papkov; Pavel Chizhov; Leopold Parts (WACV, 2025)