Profile

Thomas Hummel is a PhD candidate in the Explainable Machine Learning group and the International Max-Planck Research School for Intelligent Systems (IMPRS-IS) under the supervision of Prof. Zeynep Akata. He received his master's degree in Intelligent Adaptive Systems from the University of Hamburg in 2019 and his bachelor's degree in Bioprocess Informatics from the Weihenstephan-Triesdorf University of Applied Sciences in 2015.

Publications

• "Temporal and cross-modal attention for audio-visual zero-shot learning", Otniel-Bogdan Mercea *, Thomas Hummel *, A. Sophia Koepke, Zeynep Akata, European Conference on Computer Vision, ECCV 2022
• "Semantic Image Synthesis with Semantically Coupled VQ-Model", Stephan Alaniz *, Thomas Hummel *, Zeynep Akata, Workshop on Deep Generative Models for Highly Structured Data (DGM4HSD), ICLR 2022