A core technology cluster is typically of the order of 10 PhD students and is headed by a senior PhD student or a WASP postdoc. It is expected that the core technology groups have frequent meetings and organize joint activities such as paper reading groups etc.
The following core technology clusters are available:
- 3D Computer Vision
- Anomaly Detection
- Cryptography
- Explainable AI
- Geometric Deep Learning
- Large-Scale Optimization
- Learning from Small Data Sets and Incremental Learning
- Natural Language Processing
- Representation and Grounding
- Safety and Robustness of Autonomous Systems
- Sequential Decision-Making and Reinforcement Learning
On hold:
- Distributed Systems and Cloud Computing
- Software Analysis & Testing
- Causality & Causal Inference
- Distributed Systems and Cloud Computing
- Formal and Empirical Aspects of Agent Societies
- Generative Models (GANs, VAEs, …
- Complex Systems
- Multimodal Machine Learning (language/vision)
- Multi-task and Transfer Learning
- Privacy-Enhancing Processing
- Theoretical Aspects of “Non-Deep” Learning
- Theoretical Aspects of Deep Learning
- Security and Privacy-Aware Learning
- Mathematical foundations of AI other than ML
- Probabilistic Modeling
