Don’t Fix the Basis – Learn It: Spectral Representation with Adaptive Basis Learning for PDEs

CATO: Charted Attention for Neural PDE Operators

SpectraKAN: Conditioning Spectral Operators

Product Interaction: An Algebraic Formalism for Deep Learning Architectures

DNA-Prior: Unsupervised Denoise Anything via Dual-Domain Prior

LEGATO: Good Identity Unlearning Is Continuous

PDE Solvers Should Be Local: Fast, Stable Rollouts with Learned Local Stencils

NeuTSFlow: Modeling Continuous Functions Behind Time Series Forecasting

Deep Spectral Prior

RSFR: A Coarse-to-Fine Reconstruction Framework for Diffusion Tensor Cardiac MRI with Semantic-Aware Refinement

ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series Forecasting

NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning

Bilevel Hypergraph Networks for Multi-Modal Alzheimer’s Diagnosis

MambaMIR: An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation

TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations

Traffic Video Object Detection using Motion Prior

MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening

PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation

Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy

Delving into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings

Deep Reflection Prior

CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification

Dim the Lights! — Low-Rank Prior Temporal Data for Specular-Free Video Recovery

You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors

Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging

Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning

A Latent Diffusion for Stable Frame Interpolation

ProSMA-UNet: Decoder Conditioning for Proximal-Sparse Skip Feature Selection

Mind the Gap: Transferring Labels to Align Object Detection Datasets

Decentralized Attention Fails Centralized Signals: Rethinking Transformers for Medical Time Series

A Sliding Layer Merging Method for Efficient Depth-Wise Pruning in LLMs

Moving Beyond Functional Connectivity: Time-Series Modeling for fMRI-Based Brain Disorder Classification

Training-Free Test-Time Adaptation with Brownian Distance Covariance in Vision-Language Models

Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs

Training-Free Dual Hyperbolic Adapters for Better Cross-Modal Reasoning

A Fourier Neural Operator Approach for Modelling Exciton-Polariton Condensate Systems

Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation

Brain age prediction and early neurodegeneration detection using contrastive learning on brain biomechanics: a retrospective, multicentre study

D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction

Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems

HGIB: Prognosis for Alzheimer’s Disease via Hypergraph Information Bottleneck

Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis

VesSAM: Efficient Multi-Prompting for Segmenting Complex Vessel

Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation

Motion Constrained Point Cloud Matching for Maritime Tracking

MAMBA4D: Efficient Long-Sequence Point CloudVideo Understanding with DisentangledSpatial-Temporal State Space Models

Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey

DiffMIC-v2: Medical Image Classification via Improved Diffusion Network

Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction

Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations

TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation

Single-Shot Plug-and-Play Methods for Inverse Problems

Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba

Training-Free Feature Reconstruction with Sparse Optimization for Vision-Language Models

Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation

Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization

LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations

Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling

Optimised Propainter for Video Diminished Reality Inpainting

The Missing U for Efficient Diffusion Models

STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution

Continuous U-Net: Faster, Greater and Noiseless

Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal

Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study

NorMatch: Matching Normalizing Flows with Classifiers for Semi-Supervised Learning

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Contrastive Registration for Unsupervised Medical Image Segmentation

Beyond U: Making Diffusion Models Faster & Lighter

Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation

CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?

DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification

Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness

SCOTCH and SODA: A Transformer Video Shadow Detection Framework

ViGU: Vision GNN U-Net for Fast MRI

Gray Whale Detection in Satellite Imagery using Deep Learning

Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification

Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification

A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation

Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting

TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems

HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation

GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays

Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis

Learning Optical Flow for Fast MRI Reconstruction

Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution

Rethinking Medical Image Reconstruction via Shape Prior, Going Deeper and Faster: Deep Joint Indirect Registration and Reconstruction

Dynamic Spectral Residual Superpixels

The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification

Controllable Image Processing via Adaptive FilterBank Pyramid

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification

RainFlow: Optical Flow under Rain Streaks and Rain Veiling Effect

GraphXNET – Chest X-Ray Classification Under Extreme Minimal Supervision

Mirror, Mirror, on the Wall, Who’s Got the Clearest Image of Them All? − A Tailored Approach to Single Image Reflection Removal

Semi-supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification

ReTouchImg: Fusioning From-Local-to-Global Context Detection and Graph Data Structures for Fully-Automatic Specular Reflection Removal for Endoscopic Images

Multi-tasking to Correct: Motion-CompensatedMRI via Joint Reconstruction and Registration

Motion Correction Resolved for MRI via Multi-Tasking: A Simultaneous Reconstruction and Registration Approach

Peekaboo – Where are the Objects? Structure Adjusting Superpixels

CS+M: A Simultaneous Reconstruction and Motion Estimation Approach for Improving Undersampled MRI Reconstruction

Sensory Substitution for Force Feedback Recovery: A Perception Experimental Study

Sliding to predict: Vision-based beating heart motion estimation by modeling temporal interactions

Robust Cardiac Motion Estimation using Ultrafast Ultrasound Data: A Low-Rank Topology-Preserving Approach

Towards Retrieving Force Feedback in Robotic-Assisted Surgery: A Supervised Neuro-Recurrent-Vision Approach

Sight to Touch: 3D Diffeomorphic Deformation Recovery with Mixture Components for Perceiving Forces in Robotic-Assisted Surgery

Escaping specularity: recovering specular-free video sequences from rank-constrained data

Towards Estimating Cardiac Motion Using Low-Rank Representation and Topology Preservation for Ultrafast Ultrasound Data

A Deep-Neuro-Fuzzy Approach for Estimating the Interaction Forces in Robotic Surgery

Exploring the Effects of Dimensionality Reduction in Deep Networks for Force Estimation in Robotic-Assisted Surgery

Force-Feedback Sensory Substitution Using Supervised Recurrent Learningfor Robotic-Assisted Surgery

Automatic and Robust Single-Camera Specular Highlight Removal in Cardiac Images

Sensorless force estimation using a neuro-vision-based approach for robotic-assisted surgery