Lukas Klein
@lukaskln.bsky.social
🦠🧬💻 AI in Life Sciences / PostDoc at EPFL / ETH Zürich PhD
In her talk, Charlotte will share insights into the fields of Virtual Cells and Digital Twins, highlighting how AI is shaping personalized cancer therapies through advanced simulations of cellular behavior and patient-specific outcomes.
January 8, 2025 at 12:50 PM
In her talk, Charlotte will share insights into the fields of Virtual Cells and Digital Twins, highlighting how AI is shaping personalized cancer therapies through advanced simulations of cellular behavior and patient-specific outcomes.
🤔 Curiously, the emerging top-performing method is not examined in any relevant related study.
Happy to discuss the results during the conference!
Paper: arxiv.org/abs/2409.16756
Benchmark: github.com/IML-DKFZ/latec
(3/3)
Happy to discuss the results during the conference!
Paper: arxiv.org/abs/2409.16756
Benchmark: github.com/IML-DKFZ/latec
(3/3)
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
Explainable AI (XAI) is a rapidly growing domain with a myriad of proposed methods as well as metrics aiming to evaluate their efficacy. However, current studies are often of limited scope, examining ...
arxiv.org
December 3, 2024 at 1:08 PM
🤔 Curiously, the emerging top-performing method is not examined in any relevant related study.
Happy to discuss the results during the conference!
Paper: arxiv.org/abs/2409.16756
Benchmark: github.com/IML-DKFZ/latec
(3/3)
Happy to discuss the results during the conference!
Paper: arxiv.org/abs/2409.16756
Benchmark: github.com/IML-DKFZ/latec
(3/3)
🚀 Through LATEC, we showcase the risk of conflicting metrics causing unreliable rankings and propose a more robust evaluation scheme. We critically evaluated 17 XAI methods across 20 metrics in 7,560 unique setups, including varied architectures & input modalities.
(2/3)
(2/3)
December 3, 2024 at 1:08 PM
🚀 Through LATEC, we showcase the risk of conflicting metrics causing unreliable rankings and propose a more robust evaluation scheme. We critically evaluated 17 XAI methods across 20 metrics in 7,560 unique setups, including varied architectures & input modalities.
(2/3)
(2/3)