Farnoush Rezaei Jafari
Farnoush Rezaei Jafari
Doctoral Researcher
Farnoush Rezaei Jafari is a research associate in the Machine Learning / Intelligent Data analysis group at Technische Universität Berlin. She obtained an M.Sc. in Computer Science from TU Berlin in 2021.
- Explainable AI
- Efficient Machine Learning
- Generative Models
Mina Jamshidi Idaji, Julius Hense, Tom Neuhäuser, Augustin Krause, Yanqing Luo, Oliver Eberle, Thomas Schnake, Laure Ciernik, Farnoush Rezaei Jafari, Reza Vahidimajd, Jonas Dippel, Christoph Walz, Frederick Klauschen, Andreas Mock, Klaus-Robert Müller
Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology
Farnoush Rezaei Jafari, Oliver Eberle, Ashkan Khakzar, Neel Nanda
RelP: Faithful and Efficient Circuit Discovery in Language Models via Relevance Patching
Farnoush Rezaei Jafari, Oliver Eberle, Ashkan Khakzar, Neel Nanda
RelP: Faithful and Efficient Circuit Discovery via Relevance Patching
Thomas Schnake, Farnoush Rezaei Jafaria, Jonas Lederer, Ping Xiong, Shinichi Nakajima, Stefan Gugler, Grégoire Montavon, Klaus-Robert Müller
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle
MambaLRP: Explaining Selective State Space Sequence Models
Symbolic XAI
Researchers at BIFOLD have been exploring how to make AI explain itself in the same way, people explain themselves. The team’s work focuses on making AI predictions as clear and intuitive as a human explanation.