Titles and abstracts are available in the workshop booklet (to appear)
Contributed Talks
Day 1
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Unsupervised Residual Plug-and-Play for Image Super-Resolution with Adaptation to Ultrasound
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Self-supervised regularized deep-learning for reconstruction in digital in-line holographic microscopy
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Kirchhoff forests for Graph Linear Algebra
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LATINO-PRO: LAtent consisTency INverse sOlver with PRompt Optimization
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An efficient and guaranteed scheme for posterior sampling in inverse problem based on prior diffusion model
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Manifold-Aware Langevin Purification for Flow-based Medical Inverse Problem Solvers
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Deep-learning based Plug-And-Play methods for CT reconstruction
Day 2
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Efficient and guaranteed posterior sampling based on diffusion prior
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On the impact of the parametrization of deep convolutional neural networks on post-training quantization
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Neural network approach for inference of nonlinear mixed effect models based on ordinary differential equations
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Incompressible neural networks with application to image denoising
Poster – Day 2 (12:15–14:30)
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[C006]
Better to denoise a weak noise, the power of conservative diffusion models
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[C007]
Modeling strategies for speech enhancement in the latent space of a neural audio codec
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[C011]
AI Models for Early Type 2 Diabetes Prediction
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[C012]
Comparative Evaluation of Vision Transformer Architectures for Automatic Wheat Disease Detection
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[C013]
MLEM as a Bregman mirror descent
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[C014]
Learning noise-adaptive attention for microtubule segmentation in fluorescence microscopy images
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[C016]
Unrolled MAPEM for SPECT reconstruction
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[C017]
Bi-Level Optimization with Learned Preconditioning: Application to EEG Source Imaging
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[C018]
Optimization Strategies for Distance-Encoding Neural Networks: Evolutionary vs. Gradient-Based Approaches in Data-Scarce Medical Applications
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[C019]
SPECT with a Compton camera: image reconstruction challenges and deep learning perspectives
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[C020]
Recent Advances in Mediated Uncoupled Learning
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[C021]
Anisotropy-Aware Strategy for Robust Deep Learning-Based Particle Picking in 3D Cellular Cryo-Electron Tomogram
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[C022]
A New Method to Accelerate SVM Resolution via Support Vector Identification
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[C023]
Safe tightness identification between ℓ0-penalized problem and its convex relaxation
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[C024]
Flow Matching for Microtubule Segmentation in Noisy Microscopy Images
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[C025]
Impact of CT Machine Parameters on the Efficacy of Hybrid-ODPS-driven Material Decomposition
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[C027]
A Complete Pipeline of Multi-view Photometric Stereo
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[C029]
Comparing generative models with an end-to-end approach for solving inverse problems
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[C030]
Numerical Approximation of some Inverse Problems with Optimization Approach based on Metaheuristic Approaches
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[C033]
Deep Equilibrium models for hyper-parameter tuning in regularized PET reconstruction
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[C034]
3D CT-free PET Reconstruction using Diffusion Models
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[C035]
A Hierarchical Likelihood Model for Non-linear Inverse Problems under Additive and Multiplicative noise
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[C037]
Icecream: High-Fidelity Equivariant Cryo-Electron Tomography