Thomas Schmid

22 papers A* 1B 2C 1Journal 5Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Bridging physical constraints and deep generative models via physics-aware normalizing flows.
Neurocomputing
Benjamin Schindler, Melle Mendikowski, Thomas Schmid
2025 J jnl
Deep dive into KABR: a dataset for understanding ungulate behavior from in-situ drone video.
Multim. Tools Appl.
Maksim Kholiavchenko, Jenna Kline, Maksim Kukushkin, Otto Brookes, Sam Stevens, Isla Duporge, Alec Sheets, Reshma Ramesh Babu, Namrata Banerji, Elizabeth G. Campolongo, Matthew J. Thompson, Nina Van Tiel, Jackson Miliko, Eduardo Bessa, Majid Mirmehdi, Thomas Schmid, Tanya Y. Berger-Wolf, Daniel I. Rubenstein, Tilo Burghardt, Charles V. Stewart
2025 — conf
Multi-dependence Conditional Vector Boosting Categorical Fidelity in Tabular-Data GANs.
IDEAL (1)
Melle Mendikowski, Benjamin Schindler, Thomas Schmid, Ralf Möller, Mattis Hartwig
2025 A* conf
The PanAf-FGBG Dataset: Understanding the Impact of Backgrounds in Wildlife Behaviour Recognition.
CVPR
Otto Brookes, Maksim Kukushkin, Majid Mirmehdi, Colleen Stephens, Paula Dieguez, Thurston C. Hicks, Sorrel Jones, Kevin Lee, Maureen S. McCarthy, Amelia Meier, Emmanuelle Normand, Erin G. Wessling, Roman M. Wittig, Kevin Langergraber, Klaus Zuberbühler, Lukas Boesch, Thomas Schmid, Mimi Arandjelovic, Hjalmar S. Kühl, Tilo Burghardt
2025 J jnl
The PanAf-FGBG Dataset: Understanding the Impact of Backgrounds in Wildlife Behaviour Recognition.
CoRR
Otto Brookes, Maksim Kukushkin, Majid Mirmehdi, Colleen Stephens, Paula Dieguez, Thurston C. Hicks, Sorrel Jones, Kevin Lee, Maureen S. McCarthy, Amelia Meier, Emmanuelle Normand, Erin G. Wessling, Roman M. Wittig, Kevin Langergraber, Klaus Zuberbühler, Lukas Boesch, Thomas Schmid, Mimi Arandjelovic, Hjalmar S. Kühl, Tilo Burghardt
2025 — conf
When to Use Discriminator Ensembles? Cross-Domain Evidence of Multi-Adversarial Learning.
IDEAL (1)
Benjamin Schindler, Melle Mendikowski, Thomas Schmid, Sam Verboven
2024 — conf
BiCAE - A Bimodal Convolutional Autoencoder for Seed Purity Testing.
ECML/PKDD (10)
Maksim Kukushkin, Martin Bogdan, Thomas Schmid
2024 — conf
BiMAE - A Bimodal Masked Autoencoder Architecture for Single-Label Hyperspectral Image Classification.
CVPR Workshops
Maksim Kukushkin, Martin Bogdan, Thomas Schmid
2024 B conf
Physics-Aware Normalizing Flows: Leveraging Electric Circuit Models in Adversarial Learning.
ESANN
Benjamin Schindler, Thomas Schmid
2023 — conf
Canola seed or not? Autoencoder-based Anomaly Detection in AgriculturalSeedProduction.
GI-Jahrestagung
Maksim Kukushkin, Matthias Enders, Reinhard Kaschuba, Martin Bogdan, Thomas Schmid
2023 — ch.
Constructivist Machine Learning.
Compendium of Neurosymbolic Artificial Intelligence
Thomas Schmid
2023 — conf
Improved Techniques for Training Tabular GANs Using Cramer's V Statistics.
Canadian AI
Melle Mendikowski, Benjamin Schindler, Thomas Schmid, Ralf Möller, Mattis Hartwig
2023 J jnl
Machine learning in AI Factories - five theses for developing, managing and maintaining data-driven artificial intelligence at large scale.
it Inf. Technol.
Wolfgang Hildesheim, Taras Holoyad, Thomas Schmid
2023 C conf
On optimizing morphological neural networks for hyperspectral image classification.
ICMV
Maksim Kukushkin, Martin Bogdan, Thomas Schmid
2021 — conf
Batch-like Online Learning for More Robust Hybrid Artificial Intelligence: Deconstruction as a Machine Learning Process.
AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering
Thomas Schmid
2021 J jnl
The AI Methods, Capabilities and Criticality Grid.
Künstliche Intell.
Thomas Schmid, Wolfgang Hildesheim, Taras Holoyad, Kinga Schumacher
2020 — conf
Using Learning Algorithms to Create, Exploit and Maintain Knowledge Bases: Principles of Constructivist Machine Learning.
AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1)
Thomas Schmid
2019 — conf
Deconstructing the Final Frontier of Artificial Intelligence: Five Theses for a Constructivist Machine Learning.
AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering
Thomas Schmid
2014 — conf
Automated Quantification of the Relation between Resistor-capacitor Subcircuits from an Impedance Spectrum.
BIOSIGNALS
Thomas Schmid, Dorothee Günzel, Martin Bogdan
2014 — conf
Macht "Big Data" synthetische Datensätze überflüssig?
Informatiktage
Thomas Schmid
2013 B conf
Efficient prediction of x-axis intercepts of discrete impedance spectra.
ESANN
Thomas Schmid, Dorothee Günzel, Martin Bogdan
2010 — conf
Using an Artificial Neural Network to Determine Electrical Properties of Epithelia.
ICANN (1)
Thomas Schmid, Dorothee Günzel, Martin Bogdan