Prof. Islem Rekik — Research Profile
Imperial College London · Department of Computing
About
임페리얼 칼리지 런던 컴퓨터학과 소속 Islem Rekik 교수의 등록된 연구 분야는 Machine learning, deep learning, predictive intelligence in medicine, network neuroscience입니다.
Research keywords
Recent papers
- GNN-CB: A Graph Neural Network Competition Benchmark for Human and LLM EvaluationPreprintarXiv (Cornell University) · Oct 4
- Knowledge distillation in medical imaging: A comprehensive survey of trends, challenges, and opportunitiesInformation Fusion · Sep 27
From OpenAlex · papers whose author affiliation matches this university
Labs doing related research
Labs that recently published on topics this lab's recent papers share
Jun Wang 교수 연구실
University College London · Department of Computer Science
iSDFT: Information-Proximal Self-Distillation for Continual Learning in LLMsPreprintarXiv (Cornell University) · Sep 21Shared topic: Domain Adaptation and Few-Shot Learning
Yarin Gal 교수 연구실
University of Oxford · Department of Computer Science
Learning Dynamics of Continual Learning: A Unified View of Data Attribution, Forgetting, and Plasticity LossPreprintarXiv (Cornell University) · Sep 27Shared topic: Domain Adaptation and Few-Shot Learning
Michael Bronstein 교수 연구실
University of Oxford · Department of Computer Science
Interfaces and Modules: A Scalable Representation for Weight-Space Learning across ArchitecturesNewPreprintarXiv (Cornell University) · Oct 15Shared topic: Advanced Neural Network Applications
Other labs in this department
- Abbas Edalat 교수 연구실
Computational geometry, optimization theory, game theory
- Alastair Donaldson 교수 연구실
Formal verification, software performance optimization
- Aldo Faisal 교수 연구실
Neurotechnology, machine learning, algorithmic behavior prediction
- Alessandra Russo 교수 연구실
Computational logic, logic-based machine learning, autonomous systems
- Alessio Lomuscio 교수 연구실
AI verification, computer vision validation, certified learning
- Andrew Davison 교수 연구실
Computer vision, robotics, SLAM, augmented reality