Sidney Bender
Sidney Bender
Sidney Bender, Benedikt Kunz, Ahmed Zeid, Shinichi Nakajima, Klaus-Robert Müller, Marco Morik
Towards Fast and Disentangled Counterfactuals for Visual Foundation Models
David Bechtoldt, Sidney Bender
Faithful, Sufficient and Understandable: Rethinking Graph Counterfactual Explanations via Discrete Diffusion Inversion
Ahmed Zeid, Sidney Bender
SCE-LITE-HQ: Smooth visual counterfactual explanations with generative foundation models
Weronika Kłos, Sidney Bender, Lukas Kades
Protein Counterfactuals via Diffusion-Guided Latent Optimization
Sidney Bender, Marco Morik
Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models
BIFOLD researchers present three papers at ICLR 2024
The International Conference on Learning Representations (ICLR) is a Core-A gathering of experts who are dedicated to advancing a branch of artificial intelligence known as representation learning, which is also called deep learning.