Visual Intelligence aims to be the lead provider of novel deep learning-based solutions for cutting-edge complex image analysis. We answer innovation needs shared across a consortium of corporate and public user partners and beyond. Our research spans core AI methodology and domain-driven visual intelligence in medicine and health, marine science, energy, and earth observation.
| Research challenge | Focus |
|---|---|
| 📉 Limited training data | Learning from scarce, weak, partial, imbalanced, or otherwise constrained supervision. |
| 🧩 Context and dependencies | Modelling structure across space, time, views, modalities, objects, and tasks. |
| 📊 Confidence and uncertainty | Estimating uncertainty, information, calibration, and confidence in visual intelligence systems. |
| 🔍 Explainability and reliability | Building models and evaluation methods that are interpretable, robust, trustworthy, and reliable. |
| Innovation area | Focus |
|---|---|
| 🩺 Medicine and health | Digital pathology, cardiac imaging, mammography, CT/X-ray, PET, and clinical visual decision support. |
| 🌊 Marine science | Echosounder data, underwater exploration, and marine monitoring. |
| ⚡ Energy | Power line inspection, microfossil analysis, and uncertainty-aware energy applications. |
| 🛰️ Earth observation | SAR, multimodal remote sensing, land cover mapping, sea ice, and change detection. |
Visual Intelligence is in ongoing collaboration with The Alan Turing Institute, the British Antarctic Survey, and the University of Cambridge on AI powered sea ice forcasting. Detailed information on the project as well as links to corresponding GitHub repositories can be found on the IceNet website.
BCRBench is an open-source benchmark for breast cancer risk prediction from mammography. It provides a unified, reproducible framework for training and evaluating state-of-the-art deep learning models using standardized preprocessing, inference, and evaluation protocols. The project invites research communities to contribute their own models through a common interface, helping to advance AI-based mammography risk prediction in a transparent and comparable manner. Detailed information on how to contribute can be found on the BCRBench documentation.
If you have questions or remarks to any of the Visual Intelligence repositories, or if you are interested in a collaboration, please open a Discussion.
| Repository | Formal category |
|---|---|
| Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction | 🧩 Context and dependencies / 🩺 Medicine and health |
| RELAX: Representation Learning Explainability | 🔍 Explainability and reliability |
| The Fossil Frontier: An answer to the 3-billion fossil question | 📉 Limited training data / ⚡ Energy |
Papers can appear in both views to make the index useful from either direction.
🩺 Medicine and health (37 publications)
| Year | Topic | Research challenge | Publication | Code / resource |
|---|---|---|---|---|
| 2026 | Mammography | Context and dependencies | Longitudinal Multi-View Modeling for Breast Cancer Risk Prediction (paper) | Code |
| 2026 | Dynamic PET | Limited training data | A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging (paper) | |
| 2026 | General | Limited training data | Comparing Foundation Models for Medical Images: A Study on Limited Data and Generalization (paper) | |
| 2026 | Cardiac | Context and dependencies | Spatio-Temporal Landmark Detection via Selective Fine-Tuning of Echocardiography Foundation Models (paper) | Code |
| 2025 | Digital Pathology | Explainability and reliability | A lightweight and extensible cell segmentation and classification model for H&E-stained cancer whole slide images (paper) | |
| 2025 | Mammography | Context and dependencies | Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance (paper) | |
| 2025 | Digital Pathology | Limited training data | Fast TILs - A pipeline for efficient TILs estimation in non-small cell lung cancer (paper) | Code |
| 2025 | Mammography | Confidence and uncertainty | Modelling Uncertainty in Graph Convolutional Networks for Edge Detection in Mammograms (paper) | |
| 2025 | Cardiac | Context and dependencies | Motion-Compensated Interpolation in Echocardiography: A Lie Advection-Based Approach (paper) | |
| 2025 | Mammography | Context and dependencies | Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction (paper) | Code |
| 2025 | General | Explainability and reliability | Tied Prototype Model for Few-Shot Medical Image Segmentation (paper) | Code |
| 2025 | Mammography | Context and dependencies | VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction (paper) | Code |
| 2025 | Cardiac | Limited training data | WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements (paper) | |
| 2024 | CT and X-ray | Limited training data | An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images (paper) | |
| 2024 | Digital Pathology | Explainability and reliability | Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology (paper) | Code |
| 2024 | Others | Confidence and uncertainty | BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck (paper) | |
| 2024 | Digital Pathology | Context and dependencies | Cross-modality sub-image retrieval using contrastive multimodal image representations (paper) | Code |
| 2024 | Dynamic PET | Limited training data | Deep learning derived input function in dynamic [18F]FDG PET imaging of mice (paper) | |
| 2023 | CT and X-ray | Limited training data | A clinically motivated self-supervised approach for content-based image retrieval of CT liver images (paper) | Code |
| 2023 | Mammography | Explainability and reliability | A two-stage mammography classification model using explainable-AI for ROI detection (paper) | |
| 2023 | General | Limited training data | ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement (paper) | |
| 2023 | Motion and Pose Estimation | Context and dependencies | Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos (paper) | Code |
| 2023 | General | Explainability and reliability | Federated Partially Supervised Learning With Limited Decentralized Medical Images (paper) | |
| 2023 | Cardiac | Context and dependencies | Reverberation Suppression in Echocardiography Using a Causal Convolutional Neural Network (paper) | |
| 2023 | CT and X-ray | Limited training data | Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation (paper) | Code |
| 2023 | CT and X-ray | Limited training data | View it like a radiologist: Shifted windows for deep learning augmentation of CT images (paper) | Code |
| 2022 | Mammography | Explainability and reliability | A mammography classification model trained from image labels only (paper) | |
| 2022 | Digital Pathology | Limited training data | A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images (paper) | Code 1, Code 2, Code 3 |
| 2022 | General | Limited training data | Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels (paper) | |
| 2022 | Cardiac | Limited training data | Automatic Detection of Aortic Valve Events Using Deep Neural Networks on Cardiac Signals From Epicardially Placed Accelerometer (paper) | Code |
| 2022 | CT and X-ray | Explainability and reliability | Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation (paper) | |
| 2022 | General | Limited training data | Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images (paper) | |
| 2022 | Cardiac | Context and dependencies | Mitral Annulus Segmentation and Anatomical Orientation Detection in TEE Images Using Periodic 3D CNN (paper) | |
| 2022 | Diabetic Retinopathy | Limited training data | To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy (paper) | Code |
| 2022 | General | Explainability and reliability | Towards robust partially supervised multi-structure medical image segmentation on small-scale data (paper) | |
| 2021 | Dynamic PET | Limited training data | Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function (paper) | |
| 2021 | Digital Pathology | Explainability and reliability | Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing (paper) | |
| 2021 | General | Context and dependencies | Self-supervised Multi-task Representation Learning for Sequential Medical Images (paper) |
🌊 Marine science (4 publications)
| Year | Topic | Research challenge | Publication | Code / resource |
|---|---|---|---|---|
| 2025 | General | Limited training data | Leveraging Foundation Model Adapters to Enable Robust and Semantic Underwater Exploration (paper) | |
| 2023 | General | Context and dependencies | A Contextually Supported Abnormality Detector for Maritime Trajectories (paper) | |
| 2023 | General | Limited training data | Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data (paper) | Code |
| 2021 | General | Limited training data | Semi-supervised target classification in multi-frequency echosounder data (paper) |
⚡ Energy (6 publications)
| Year | Topic | Research challenge | Publication | Code / resource |
|---|---|---|---|---|
| 2025 | Microfossils | Confidence and uncertainty | Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts (paper) | Code |
| 2025 | Microfossils | Limited training data | The Fossil Frontier: An answer to the 3-billion fossil question (paper) | Code |
| 2025 | Power line inspection | Limited training data | WOODWORK: A deep-learning based framework for woodpecker damage detection in powerline inspection (paper) | |
| 2024 | Power Line Inspection | Limited training data | LSNetv2: Improving weakly supervised power line detection with bipartite matching (paper) | |
| 2024 | Microfossils | Explainability and reliability | The 3-billion fossil question: How to automate classification of microfossils (paper) | Code |
| 2021 | Microfossils | Context and dependencies | Instance Segmentation of Microscopic Foraminifera (paper) |
🛰️ Earth observation (7 publications)
| Year | Topic | Research challenge | Publication | Code / resource |
|---|---|---|---|---|
| 2025 | SAR | Context and dependencies | Joint Despeckling and Thermal Noise Compensation: Application to Sentinel-1 Images of the Arctic (paper) | GitLab, Code |
| 2024 | General | Limited training data | Better, Not Just More: Data-centric machine learning for Earth observation (paper) | |
| 2023 | SAR | Explainability and reliability | SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel-1/AMSR-2 for Sea Ice Classification (paper) | |
| 2022 | SAR | Context and dependencies | A Generalized Geodesic Distance-Based Approach for Analysis of SAR Observations Across Polarimetric Modes (paper) | Code |
| 2022 | Multimodal earth observation | Limited training data | Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images (paper) | Code |
| 2022 | Multimodal earth observation | Context and dependencies | Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks (paper) | Code |
| 2021 | General | Context and dependencies | Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images (paper) |
📉 Limited training data (41 publications)
| Year | Topic | Innovation area | Publication | Code / resource |
|---|---|---|---|---|
| 2026 | Foundation models | Medicine and health | Comparing Foundation Models for Medical Images: A Study on Limited Data and Generalization (paper) | |
| 2026 | Dynamic PET | Limited training data | CA robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging (paper) | |
| 2025 | Unsupervised learning | AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering (paper) | Code | |
| 2025 | Domain transfer | Medicine and health | Fast TILs - A pipeline for efficient TILs estimation in non-small cell lung cancer (paper) | Code |
| 2025 | Foundation models | Marine science | Leveraging Foundation Model Adapters to Enable Robust and Semantic Underwater Exploration (paper) | |
| 2025 | Foundation models | Low-Rank Adaptations for increased Generalization in Foundation Model features (paper) | Code | |
| 2025 | Semi-supervised learning | SuperCM: Improving semi-supervised learning and domain adaptation through differentiable clustering (paper) | ||
| 2025 | General | Energy | The Fossil Frontier: An answer to the 3-billion fossil question (paper) | Code |
| 2025 | General | Medicine and health | WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements (paper) | |
| 2025 | General | Energy | WOODWORK: A deep-learning based framework for woodpecker damage detection in powerline inspection (paper) | |
| 2024 | Self-supervised learning | Medicine and health | An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images (paper) | |
| 2024 | General | Earth observation | Better, Not Just More: Data-centric machine learning for Earth observation (paper) | |
| 2024 | General | Medicine and health | Deep learning derived input function in dynamic [18F]FDG PET imaging of mice (paper) | |
| 2024 | Self-supervised learning | Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features (paper) | Code | |
| 2024 | Weakly supervised | Energy | LSNetv2: Improving weakly supervised power line detection with bipartite matching (paper) | |
| 2024 | Clustering | MAP IT to Visualize Representations (paper) | Code | |
| 2024 | General | Polar mesospheric summer echo (PMSE) multilayer properties during the solar maximum and solar minimum (paper) | ||
| 2023 | Self-supervised learning | Medicine and health | A clinically motivated self-supervised approach for content-based image retrieval of CT liver images (paper) | Code |
| 2023 | Few-shot learning | Medicine and health | ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement (paper) | |
| 2023 | Semi-supervised learning | Marine science | Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data (paper) | Code |
| 2023 | General | DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment (paper) | ||
| 2023 | Few-shot learning | Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings (paper) | Code | |
| 2023 | Self-supervised learning | On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering (paper) | Code | |
| 2023 | Self-supervised learning | Medicine and health | Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation (paper) | Code |
| 2023 | Unsupervised learning | Supercm: Revisiting Clustering for Semi-Supervised Learning (paper) | Code | |
| 2023 | General | Using Deep Learning Methods for Segmenting Polar Mesospheric Summer Echoes (paper) | ||
| 2023 | General | Medicine and health | View it like a radiologist: Shifted windows for deep learning augmentation of CT images (paper) | Code |
| 2022 | Domain transfer | Medicine and health | A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images (paper) | Code 1, Code 2, Code 3 |
| 2022 | Self-supervised learning | A self-guided anomaly detection-inspired few-shot segmentation network (paper) | ||
| 2022 | Self-supervised learning | Medicine and health | Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels (paper) | |
| 2022 | General | ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design (paper) | Resource | |
| 2022 | General | Medicine and health | Automatic Detection of Aortic Valve Events Using Deep Neural Networks on Cardiac Signals From Epicardially Placed Accelerometer (paper) | Code |
| 2022 | Unsupervised learning | Earth observation | Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images (paper) | Code |
| 2022 | General | Medicine and health | Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images (paper) | |
| 2022 | Self-supervised learning | M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining (paper) | Dataset | |
| 2022 | Self-supervised learning | Mixing up contrastive learning: Self-supervised representation learning for time series (paper) | Code | |
| 2022 | Self-supervised learning | Medicine and health | To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy (paper) | Code |
| 2021 | General | Medicine and health | Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function (paper) | |
| 2021 | General | Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection (paper) | Code | |
| 2021 | Unsupervised learning | Reconsidering Representation Alignment for Multi-View Clustering (paper) | Code | |
| 2021 | Unsupervised learning | Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective (paper) | ||
| 2021 | Semi-supervised learning | Marine science | Semi-supervised target classification in multi-frequency echosounder data (paper) |
🧩 Context and dependencies (33 publications)
| Year | Topic | Innovation area | Publication | Code / resource |
|---|---|---|---|---|
| 2026 | Geometric learning | Medicine and health | Spatio-Temporal Landmark Detection via Selective Fine-Tuning of Echocardiography Foundation Models (paper) | Code |
| 2026 | Semantically aware segmentation | SPoT: Subpixel Placement of Tokens in Vision Transformers (paper) | Code | |
| 2025 | Geometric learning | A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering (paper) | Code | |
| 2025 | Semantically aware segmentation | A Spitting Image: Modular Superpixel Tokenization in Vision Transformers (paper) | Code | |
| 2025 | General | Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders (paper) | ||
| 2025 | Multi-task learning | Medicine and health | Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance (paper) | |
| 2025 | Semantically aware segmentation | Differentiable Hierarchical Visual Tokenization (paper) | Code | |
| 2025 | General | Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting (paper) | Code | |
| 2025 | General | Earth observation | Joint Despeckling and Thermal Noise Compensation: Application to Sentinel-1 Images of the Arctic (paper) | GitLab, Code |
| 2025 | Spatio-temporal and longitudinal information | Medicine and health | Motion-Compensated Interpolation in Echocardiography: A Lie Advection-Based Approach (paper) | |
| 2025 | Geometric learning | ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation (paper) | Code | |
| 2025 | Spatio-temporal and longitudinal information | Medicine and health | Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction (paper) | Code |
| 2025 | General | Robust Classification by Coupling Data Mollification with Label Smoothing (paper) | Code | |
| 2025 | General | Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes (paper) | Project page | |
| 2025 | Geometric learning | Medicine and health | VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction (paper) | Code |
| 2024 | Geometric learning | Medicine and health | Cross-modality sub-image retrieval using contrastive multimodal image representations (paper) | Code |
| 2024 | General | Interrogating Sea Ice Predictability with Gradients (paper) | ||
| 2024 | Multi-task learning | Leveraging tensor kernels to reduce objective function mismatch in deep clustering (paper) | Code | |
| 2024 | General | PTUS: Photo-Realistic Talking Upper-Body Synthesis via 3D-Aware Motion Decomposition Warping (paper) | Resource | |
| 2023 | General | Marine science | A Contextually Supported Abnormality Detector for Maritime Trajectories (paper) | |
| 2023 | General | Medicine and health | Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos (paper) | Code |
| 2023 | Spatio-temporal and longitudinal information | Medicine and health | Reverberation Suppression in Echocardiography Using a Causal Convolutional Neural Network (paper) | |
| 2023 | General | Selective Imputation for Multivariate Time Series Datasets with Missing Values (paper) | Dataset | |
| 2022 | General | Medicine and health | Mitral Annulus Segmentation and Anatomical Orientation Detection in TEE Images Using Periodic 3D CNN (paper) | |
| 2022 | General | Earth observation | Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks (paper) | Code |
| 2022 | General | Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning (paper) | Code | |
| 2021 | General | Energy | Instance Segmentation of Microscopic Foraminifera (paper) | |
| 2021 | General | Joint optimization of an autoencoder for clustering and embedding. (paper) | Code | |
| 2021 | General | M3D-VTON: A Monocular-to-3D Virtual Try-On Network (paper) | Code | |
| 2021 | Semantically aware segmentation | Earth observation | Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images (paper) | |
| 2021 | General | Medicine and health | Self-supervised Multi-task Representation Learning for Sequential Medical Images (paper) | |
| 2021 | General | Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN (paper) | Code |
📊 Confidence and uncertainty (15 publications)
| Year | Topic | Innovation area | Publication | Code / resource |
|---|---|---|---|---|
| 2025 | Federated and distributed learning | Addressing Label Shift in Distributed Learning via Entropy Regularization (paper) | ||
| 2025 | General | Medicine and health | Modelling Uncertainty in Graph Convolutional Networks for Edge Detection in Mammograms (paper) | |
| 2025 | General | Energy | Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts (paper) | Code |
| 2025 | General | REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability (paper) | Code | |
| 2025 | Information theory | The Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making (paper) | Code | |
| 2024 | General | Medicine and health | BrainIB: Interpretable Brain Network-Based Psychiatric Diagnosis With Graph Information Bottleneck (paper) | |
| 2024 | Information theory | Cauchy-Schwarz Divergence Information Bottleneck for Regression (paper) | Code | |
| 2024 | Information theory | On the Generalization of Stochastic Gradient Descent with Momentum (paper) | ||
| 2023 | Information theory | Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy (paper) | Code | |
| 2023 | Information theory | Discriminative multimodal learning via conditional priors in generative models (paper) | Code | |
| 2023 | General | On Measures of Uncertainty in Classification (paper) | Code | |
| 2022 | Information theory | Gated information bottleneck for generalization in sequential environments (paper) | Code | |
| 2022 | Information theory | Principle of Relevant Information for Graph Sparsification (paper) | Code | |
| 2022 | Information theory | The Kernelized Taylor Diagram (paper) | Code | |
| 2021 | Information theory | Measuring Dependence with Matrix-based Entropy Functional (paper) | Code |
🔍 Explainability and reliability (33 publications)
| Year | Topic | Innovation area | Publication | Code / resource |
|---|---|---|---|---|
| 2026 | Concepts and prototypes | Concepts' Information Bottleneck Models (paper) | ||
| 2026 | Concepts and prototypes | Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning (paper) | ||
| 2025 | General | Medicine and health | A lightweight and extensible cell segmentation and classification model for H&E-stained cancer whole slide images (paper) | |
| 2025 | General | DocVXQA: Context-Aware Visual Explanations for Document Question Answering (paper) | Code | |
| 2025 | General explainability methods | FLEXtime: Filterbank Learning to Explain Time Series (paper) | Code | |
| 2025 | Concepts and prototypes | From Colors to Classes: Emergence of Concepts in Vision Transformers (paper) | Code | |
| 2025 | General explainability methods | From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation (paper) | Code | |
| 2025 | Concepts and prototypes | Medicine and health | Tied Prototype Model for Few-Shot Medical Image Segmentation (paper) | Code |
| 2024 | General | Medicine and health | Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology (paper) | Code |
| 2024 | Federated and distributed learning | Defending Against Poisoning Attacks in Federated Learning with Blockchain (paper) | ||
| 2024 | General | DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning (paper) | ||
| 2024 | General | ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations (paper) | Code | |
| 2024 | General | Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks (paper) | ||
| 2024 | Federated and distributed learning | Mixed Nash for Robust Federated Learning (paper) | ||
| 2024 | Concepts and prototypes | Prototypical Self-Explainable Models Without Re-training (paper) | Code | |
| 2024 | General | Energy | The 3-billion fossil question: How to automate classification of microfossils (paper) | Code |
| 2024 | Concepts and prototypes | Visual Data Diagnosis and Debiasing with Concept Graphs (paper) | Code | |
| 2023 | General | Medicine and health | A two-stage mammography classification model using explainable-AI for ROI detection (paper) | |
| 2023 | Federated and distributed learning | Federated Learning under Covariate Shifts with Generalization Guarantees (paper) | ||
| 2023 | Federated and distributed learning | Medicine and health | Federated Partially Supervised Learning With Limited Decentralized Medical Images (paper) | |
| 2023 | General | RELAX: Representation Learning Explainability (paper) | Code | |
| 2023 | General | Earth observation | SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel-1/AMSR-2 for Sea Ice Classification (paper) | |
| 2023 | General | The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus (paper) | Code | |
| 2022 | General | Medicine and health | A mammography classification model trained from image labels only (paper) | |
| 2022 | General | Medicine and health | Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation (paper) | |
| 2022 | Concepts and prototypes | ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model (paper) | Code | |
| 2022 | Concepts and prototypes | This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation (paper) | Code | |
| 2022 | General | Medicine and health | Towards robust partially supervised multi-structure medical image segmentation on small-scale data (paper) | |
| 2021 | General | Medicine and health | Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing (paper) | |
| 2021 | General explainability methods | Explain and improve: LRP-inference fine-tuning for image captioning models (paper) | Code | |
| 2021 | General explainability methods | Pruning by explaining: A novel criterion for deep neural network pruning (paper) | Code | |
| 2021 | Concepts and prototypes | Towards Scalable and Unified Example-based Explanation and Outlier Detection (paper) | Code |