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20232026
most citedDiffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative Evaluation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Early Yield Prediction for Sugar Beet Fields using Satellite Data -- Learnings from Specialized Vision Transformers

Philipp Vaeth, Bhumika Laxman Sadbhave, Denise Dejon +2

Remote sensing has become an increasingly valuable tool for agricultural monitoring, particularly through the use of publicly available satellite imagery. However, effectively inte…

cs.CV2025

Sugar-Beet Stress Detection using Satellite Image Time Series

Bhumika Laxman Sadbhave, Philipp Vaeth, Denise Dejon +2

Satellite Image Time Series (SITS) data has proven effective for agricultural tasks due to its rich spectral and temporal nature. In this study, we tackle the task of stress detect…

cs.LG2025

Loss Functions in Diffusion Models: A Comparative Study

Dibyanshu Kumar, Philipp Vaeth, Magda Gregorová

Diffusion models have emerged as powerful generative models, inspiring extensive research into their underlying mechanisms. One of the key questions in this area is the loss functi…

cs.LG2025

Diffusion Classifier Guidance for Non-robust Classifiers

Philipp Vaeth, Dibyanshu Kumar, Benjamin Paassen +1

Classifier guidance is intended to steer a diffusion process such that a given classifier reliably recognizes the generated data point as a certain class. However, most classifier…

cs.LG2024

Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

Recently, several methods have leveraged deep generative modeling to produce example-based explanations of image classifiers. Despite producing visually stunning results, these met…

cs.LG2024

GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

To sample from an unconditionally trained Denoising Diffusion Probabilistic Model (DDPM), classifier guidance adds conditional information during sampling, but the gradients from c…

cs.CV2023★ 1 cited

Diffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative Evaluation

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

Latest methods for visual counterfactual explanations (VCE) harness the power of deep generative models to synthesize new examples of high-dimensional images of impressive quality.…