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

1 code implementation • 11 Aug 2023 • Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen, Magda Gregorova

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.

counterfactual Image Classification

Graph Edit Networks

1 code implementation • ICLR 2021 • Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara Eva Hammer

With this result, we hope to provide a firm theoretical basis for a next generation of time series prediction models.

Attribute Graph Generation +3

Recursive Tree Grammar Autoencoders

3 code implementations • 3 Dec 2020 • Benjamin Paassen, Irena Koprinska, Kalina Yacef

Machine learning on trees has been mostly focused on trees as input to algorithms.

Drug Discovery Time Series +1

Tree Echo State Autoencoders with Grammars

2 code implementations • 19 Apr 2020 • Benjamin Paassen, Irena Koprinska, Kalina Yacef

Tree data occurs in many forms, such as computer programs, chemical molecules, or natural language.

Time Series Time Series Prediction

Reservoir memory machines

no code implementations • 12 Feb 2020 • Benjamin Paassen, Alexander Schulz

In recent years, Neural Turing Machines have gathered attention by joining the flexibility of neural networks with the computational capabilities of Turing machines.

regression

Ontology-based Extraction of Structured Information from Publications on Preclinical Experiments for Spinal Cord Injury Treatments

no code implementations • WS 2014 • Benjamin Paassen, Andreas St{\"o}ckel, Raphael Dickfelder, Jan Philip G{\"o}pfert, Nicole Brazda, Tarek Kirchhoffer, Hans Werner M{\"u}ller, Roman Klinger, Matthias Hartung, Philipp Cimiano