Tal Arbel
14 papers · 2014–2026 · 4 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Conference Polyglot (4) π Academic Marathon (11) π Renaissance Researcher (5) πΊοΈ Taxonomy Completionist (20)
π
Academic Marathon
(11)
π
Renaissance Researcher
(5)
π
Interdisciplinary Bridge
π
Century Club
(11)
π₯
Unstoppable
(5)
π
Conference Pioneer
Conferences
MIDL (9)
MICCAI (3)
CVPR (1)
NIPS (1)
Top co-authors
Keywords
magnetic resonance imaging
(4)
uncertainty quantification
(3)
multiple sclerosis
(2)
medical image classification
(2)
domain adaptation
(1)
disease progression
(1)
multi-task learning
(1)
deep learning
(1)
probabilistic modeling
(1)
medical image analysis
(1)
in-context learning
(1)
generalization error
(1)
poisson-binomial distribution
(1)
knowledge distillation
(1)
algorithmic fairness
(1)
bilevel optimization
(1)
distributionally robust optimization
(1)
markov random field
(1)
convolutional neural network
(1)
adversarial learning
(1)
Papers
PIKACHU: Prototypical In-context Knowledge Adaptation for Clinical Heterogeneous Usage
MIDL 2026
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
MICCAI 2025
Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
MICCAI 2025
PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion
MIDL 2025
Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Free
MIDL 2025
DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual Explanations
MIDL 2024
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs
MICCAI 2024
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis
MIDL 2023
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI
MIDL 2022
On Learning Fairness and Accuracy on Multiple Subgroups
NIPS 2022
Segmentation-Consistent Probabilistic Lesion Counting
MIDL 2022
HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images
MIDL 2021
Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data
MIDL 2019
Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI
CVPR 2014