<h2>OASIcs, Volume 126, SAIA 2024</h2>
<ul>
<li>
<span class="authors">Rebekka Görge, Elena Haedecke, Maximilian Poretschkin, and Anna Schmitz</span>
<span class="title">OASIcs, Volume 126, SAIA 2024, Complete Volume</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024">10.4230/OASIcs.SAIA.2024</a>
</li>
<li>
<span class="authors">Rebekka Görge, Elena Haedecke, Maximilian Poretschkin, and Anna Schmitz</span>
<span class="title">Front Matter, Table of Contents, Preface, Conference Organization</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.0">10.4230/OASIcs.SAIA.2024.0</a>
</li>
<li>
<span class="authors">Afef Awadid and Boris Robert</span>
<span class="title">On Assessing ML Model Robustness: A Methodological Framework (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.1">10.4230/OASIcs.SAIA.2024.1</a>
</li>
<li>
<span class="authors">Marc-André Zöller, Anastasiia Iurshina, and Ines Röder</span>
<span class="title">Trustworthy Generative AI for Financial Services (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.2">10.4230/OASIcs.SAIA.2024.2</a>
</li>
<li>
<span class="authors">Ronald Schnitzer, Andreas Hapfelmeier, and Sonja Zillner</span>
<span class="title">EAM Diagrams - A Framework to Systematically Describe AI Systems for Effective AI Risk Assessment (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.3">10.4230/OASIcs.SAIA.2024.3</a>
</li>
<li>
<span class="authors">Daniel Weimer, Andreas Gensch, and Kilian Koller</span>
<span class="title">Scaling of End-To-End Governance Risk Assessments for AI Systems (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.4">10.4230/OASIcs.SAIA.2024.4</a>
</li>
<li>
<span class="authors">Joachim Iden, Felix Zwarg, and Bouthaina Abdou</span>
<span class="title">Risk Analysis Technique for the Evaluation of AI Technologies with Respect to Directly and Indirectly Affected Entities (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.5">10.4230/OASIcs.SAIA.2024.5</a>
</li>
<li>
<span class="authors">Dominik Eisl, Bastian Bernhardt, Lukas Höhndorf, and Rafal Kulaga</span>
<span class="title">SafeAI-Kit: A Software Toolbox to Evaluate AI Systems with a Focus on Uncertainty Quantification (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.6">10.4230/OASIcs.SAIA.2024.6</a>
</li>
<li>
<span class="authors">Christoph Tobias Wirth, Mihai Maftei, Rosa Esther Martín-Peña, and Iris Merget</span>
<span class="title">Towards Trusted AI: A Blueprint for Ethics Assessment in Practice (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.7">10.4230/OASIcs.SAIA.2024.7</a>
</li>
<li>
<span class="authors">Adrian Seeliger</span>
<span class="title">AI Readiness of Standards: Bridging Traditional Norms with Modern Technologies (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.8">10.4230/OASIcs.SAIA.2024.8</a>
</li>
<li>
<span class="authors">Sergio Genovesi</span>
<span class="title">Introducing an AI Governance Framework in Financial Organizations. Best Practices in Implementing the EU AI Act (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.9">10.4230/OASIcs.SAIA.2024.9</a>
</li>
<li>
<span class="authors">Sergio Genovesi, Martin Haimerl, Iris Merget, Samantha Morgaine Prange, Otto Obert, Susanna Wolf, and Jens Ziehn</span>
<span class="title">Evaluating Dimensions of AI Transparency: A Comparative Study of Standards, Guidelines, and the EU AI Act (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.10">10.4230/OASIcs.SAIA.2024.10</a>
</li>
<li>
<span class="authors">Oliver Müller, Veronika Lazar, and Matthias Heck</span>
<span class="title">Transparency of AI Systems (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.11">10.4230/OASIcs.SAIA.2024.11</a>
</li>
<li>
<span class="authors">Elisabeth Pachl, Fabian Langer, Thora Markert, and Jeanette Miriam Lorenz</span>
<span class="title">A View on Vulnerabilites: The Security Challenges of XAI (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.12">10.4230/OASIcs.SAIA.2024.12</a>
</li>
<li>
<span class="authors">Benjamin Fresz, Danilo Brajovic, and Marco F. Huber</span>
<span class="title">AI Certification: Empirical Investigations into Possible Cul-De-Sacs and Ways Forward (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.13">10.4230/OASIcs.SAIA.2024.13</a>
</li>
<li>
<span class="authors">Susanne Kuch and Raoul Kirmes</span>
<span class="title">AI Certification: An Accreditation Perspective (Practitioner Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.14">10.4230/OASIcs.SAIA.2024.14</a>
</li>
<li>
<span class="authors">Carmen Frischknecht-Gruber, Philipp Denzel, Monika Reif, Yann Billeter, Stefan Brunner, Oliver Forster, Frank-Peter Schilling, Joanna Weng, and Ricardo Chavarriaga</span>
<span class="title">AI Assessment in Practice: Implementing a Certification Scheme for AI Trustworthiness (Academic Track)</span>
<a class="doi" href="https://doi.org/10.4230/OASIcs.SAIA.2024.15">10.4230/OASIcs.SAIA.2024.15</a>
</li>
</ul>
The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.
Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode
Feedback for Dagstuhl Publishing