Fast evolutionary maximum margin clustering. - Fabian Gieseke; Tapio Pahikkala; Oliver Kramer 001 (ICML, 2009)

Resilient K-d Trees: K-Means in Space Revisited. - Fabian Gieseke; Gabriel Moruz; Jan Vahrenhold (ICDM, 2010)

Detecting Quasars in Large-Scale Astronomical Surveys. - Fabian Gieseke; Kai Lars Polsterer; Andreas Thom 001; Peter Zinn; Dominik Bomanns; Ralf-Jurgen Dettmar; Oliver Kramer 001; Jan Vahrenhold (ICMLA, 2010)

Pruning spanners and constructing well-separated pair decompositions in the presence of memory hierarchies. - Fabian Gieseke; Joachim Gudmundsson; Jan Vahrenhold (J. Discrete Algorithms, 2010)

Analysis of wind energy time series with kernel methods and neural networks. - Oliver Kramer 001; Fabian Gieseke (ICNC, 2011)

Speedy Local Search for Semi-Supervised Regularized Least-Squares. - Fabian Gieseke; Oliver Kramer 001; Antti Airola; Tapio Pahikkala (KI, 2011)

Variance Scaling for EDAs Revisited. - Oliver Kramer 001; Fabian Gieseke (KI, 2011)

Short-Term Wind Energy Forecasting Using Support Vector Regression. - Oliver Kramer 001; Fabian Gieseke (SOCO, 2011)

From supervised to unsupervised support vector machines and applications in astronomy. - Fabian Gieseke (2011)

Von überwachten zu unüberwachten Support-Vektor-Maschinen und Anwendungen in der Astronomie. - Fabian Gieseke (Ausgezeichnete Informatikdissertationen, 2012)

Unsupervised Multi-class Regularized Least-Squares Classification. - Tapio Pahikkala; Antti Airola; Fabian Gieseke; Oliver Kramer 001 (ICDM, 2012)

Sparse Quasi-Newton Optimization for Semi-supervised Support Vector Machines. - Fabian Gieseke; Antti Airola; Tapio Pahikkala; Oliver Kramer 001 (ICPRAM (1), 2012)

Evolutionary kernel density regression. - Oliver Kramer 001; Fabian Gieseke (Expert Syst. Appl., 2012)

Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification. - Fabian Gieseke; Oliver Kramer 001; Antti Airola; Tapio Pahikkala (Evol. Intell., 2012)

Resilient k-d trees: k-means in space revisited. - Fabian Gieseke; Gabriel Moruz; Jan Vahrenhold (Frontiers Comput. Sci., 2012)

Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. - Fabian Gieseke; Tapio Pahikkala; Christian Igel (ACML, 2013)

Support Vector Machines for Wind Energy Prediction in Smart Grids. - Oliver Kramer 001; Nils André Treiber; Fabian Gieseke (EnviroInfo, 2013)

Towards Non-linear Constraint Estimation for Expensive Optimization. - Fabian Gieseke; Oliver Kramer 001 (EvoApplications, 2013)

On GPU-Based Nearest Neighbor Queries for Large-Scale Photometric Catalogs in Astronomy. - Justin Heinermann; Oliver Kramer 001; Kai Lars Polsterer; Fabian Gieseke (KI, 2013)

Learning morphological maps of galaxies with unsupervised regression. - Oliver Kramer 001; Fabian Gieseke; Kai Lars Polsterer (Expert Syst. Appl., 2013)

Wind energy prediction and monitoring with neural computation. - Oliver Kramer 001; Fabian Gieseke; Benjamin Satzger (Neurocomputing, 2013)

From Supervised to Unsupervised Support Vector Machines and Applications in Astronomy. - Fabian Gieseke (Künstliche Intell., 2013)

Speedy greedy feature selection: Better redshift estimation via massive parallelism. - Fabian Gieseke; Kai Lars Polsterer; Cosmin Eugen Oancea; Christian Igel (ESANN, 2014)

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. - Fabian Gieseke; Justin Heinermann; Cosmin E. Oancea; Christian Igel (ICML, 2014)

A Framework for Data Mining in Wind Power Time Series. - Oliver Kramer 001; Fabian Gieseke; Justin Heinermann; Jendrik Poloczek; Nils André Treiber (DARE, 2014)

Fast and simple gradient-based optimization for semi-supervised support vector machines. - Fabian Gieseke; Antti Airola; Tapio Pahikkala; Oliver Kramer 001 (Neurocomputing, 2014)

On Unsupervised Training of Multi-Class Regularized Least-Squares Classifiers. - Tapio Pahikkala; Antti Airola; Fabian Gieseke; Oliver Kramer 001 (J. Comput. Sci. Technol., 2014)

Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering. - Fabian Gieseke; Tapio Pahikkala; Tom Heskes (IDA, 2015)

An Efficient Many-Core Implementation for Semi-Supervised Support Vector Machines. - Fabian Gieseke (MOD, 2015)

Nearest neighbor density ratio estimation for large-scale applications in astronomy. - Jan Kremer; Fabian Gieseke; Kim Steenstrup Pedersen; Christian Igel (Astron. Comput., 2015)

Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering. - Emille E. O. Ishida; Michele Sasdelli; Ricardo Vilalta; Michel Aguena; Vinicius C. Busti; Hugo Camacho; Arlindo M. M. Trindade; Fabian Gieseke; Rafael S. de Souza; Yabebal T. Fantaye; Paolo A. Mazzali (Astroinformatics, 2016)

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. - Kai Lars Polsterer; Fabian Gieseke; Christian Igel; Bernd Doser; Nikolaos Gianniotis (ESANN, 2016)

Massively-parallel best subset selection for ordinary least-squares regression. - Fabian Gieseke; Kai Lars Polsterer; Ashish Mahabal; Christian Igel; Tom Heskes (SSCI, 2017)

Deep-learnt classification of light curves. - Ashish Mahabal; Kshiteej Sheth; Fabian Gieseke; Akshay Pai; S. George Djorgovski; Andrew J. Drake; Matthew J. Graham (SSCI, 2017)

Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description. - Corneliu Florea; Cosmin Toca; Fabian Gieseke (WACV, 2017)

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. - Jan Kremer; Kristoffer Stensbo-Smidt; Fabian Gieseke; Kim Steenstrup Pedersen; Christian Igel (IEEE Intell. Syst., 2017)

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices. - Fabian Gieseke; Cosmin E. Oancea; Christian Igel (Knowl. Based Syst., 2017)

Training Big Random Forests with Little Resources. - Fabian Gieseke; Christian Igel (KDD, 2018)

Massively-parallel break detection for satellite data. - Malte von Mehren; Fabian Gieseke; Jan Verbesselt; Sabina Rosca; Stéphanie Horion; Achim Zeileis (SSDBM, 2018)

Bigger Buffer k-d Trees on Multi-Many-Core Systems. - Fabian Gieseke; Cosmin Eugen Oancea; Ashish Mahabal; Christian Igel; Tom Heskes (VECPAR, 2018)

Artistic movement recognition by consensus of boosted SVM based experts. - Corneliu Florea; Fabian Gieseke (J. Vis. Commun. Image Represent., 2018)

Magnitude and Uncertainty Pruning Criterion for Neural Networks. - Vinnie Ko; Stefan Oehmcke; Fabian Gieseke (IEEE BigData, 2019)

Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data. - Stefan Oehmcke; Christoffer Thrysøe; Andreas Borgstad; Marcos Antonio Vaz Salles; Martin Brandt; Fabian Gieseke (IEEE BigData, 2019)

Learning Selection Masks for Deep Neural Networks. - Stefan Oehmcke; Fabian Gieseke (CoRR, 2019)

Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees. - Cosmin Eugen Oancea; Ties Robroek; Fabian Gieseke (IEEE BigData, 2020)

Creating cloud-free satellite imagery from image time series with deep learning. - Stefan Oehmcke; Tzu-Hsin Karen Chen; Alexander V. Prishchepov; Fabian Gieseke (BigSpatial@SIGSPATIAL, 2020)

Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values. - Fabian Gieseke; Sabina Rosca; Troels Henriksen; Jan Verbesselt; Cosmin E. Oancea (ICDE, 2020)

Attention as Activation. - Yimian Dai; Stefan Oehmcke; Fabian Gieseke; Yiquan Wu; Kobus Barnard (ICPR, 2020)

Inferring astrophysical X-ray polarization with deep learning. - Nikita Moriakov; Ashwin Samudre; Michela Negro; Fabian Gieseke; Sydney Otten; Luc Hendriks (CoRR, 2020)

Implementation of BFASTmonitor Algorithm on Google Earth Engine to Support Large-Area and Sub-Annual Change Monitoring Using Earth Observation Data. - Eliakim Hamunyela; Sabina Rosca; Andrei Mîrt; Eric Engle; Martin Herold 001; Fabian Gieseke; Jan Verbesselt (Remote. Sens., 2020)

Estimating Forest Canopy Height With Multi-Spectral and Multi-Temporal Imagery Using Deep Learning. - Stefan Oehmcke; Thomas Nyegaard-Signori; Kenneth Grogan; Fabian Gieseke (IEEE BigData, 2021)

Dataset Sensitive Autotuning of Multi-versioned Code Based on Monotonic Properties - Autotuning in Futhark. - Philip Munksgaard; Svend Lund Breddam; Troels Henriksen; Fabian Gieseke; Cosmin E. Oancea (TFP, 2021)

Attentional Feature Fusion. - Yimian Dai; Fabian Gieseke; Stefan Oehmcke; Yiquan Wu; Kobus Barnard (WACV, 2021)

Deep learning based 3D point cloud regression for estimating forest biomass. - Stefan Oehmcke; Lei Li 050; Jaime C. Revenga; Thomas Nord-Larsen; Katerina Trepekli; Fabian Gieseke; Christian Igel (SIGSPATIAL/GIS, 2022)

Input Selection for Bandwidth-Limited Neural Network Inference. - Stefan Oehmcke; Fabian Gieseke (SDM, 2022)

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. - Tianfang Zhang; Lei Li 050; Christian Igel; Stefan Oehmcke; Fabian Gieseke; Zhenming Peng (CoRR, 2022)

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods. - Jaime C. Revenga; Katerina Trepekli; Stefan Oehmcke; Rasmus Jensen; Lei Li 050; Christian Igel; Fabian Gieseke; Thomas Friborg (Remote. Sens., 2022)

Seasonal-Trend Time Series Decomposition on Graphics Processing Units. - Dmitry Serykh; Stefan Oehmcke; Cosmin E. Oancea; Dainius Masiliunas; Jan Verbesselt; Yan Cheng; Stéphanie Horion; Fabian Gieseke; Nikolaj Hinnerskov (IEEE Big Data, 2023)

End-to-End Neural Network Training for Hyperbox-Based Classification. - Denis Martins 001; Christian Lülf; Fabian Gieseke (ESANN, 2023)

RapidEarth: A Search-by-Classification Engine for Large-Scale Geospatial Imagery. - Christian Lülf; Denis Mayr Lima Martins; Marcos Antonio Vaz Salles; Yongluan Zhou; Fabian Gieseke (SIGSPATIAL/GIS, 2023)

BuildSeg: A General Framework for the Segmentation of Buildings. - Lei Li 050; Tianfang Zhang; Stefan Oehmcke; Fabian Gieseke; Christian Igel (CoRR, 2023)

Fast Search-By-Classification for Large-Scale Databases Using Index-Aware Decision Trees and Random Forests. - Christian Lülf; Denis Mayr Lima Martins; Marcos Antonio Vaz Salles; Yongluan Zhou; Fabian Gieseke (Proc. VLDB Endow., 2023)

Estimating Canopy Height at Scale. - Jan Pauls; Max Zimmer; Una M. Kelly; Martin Schwartz; Sassan Saatchi; Philippe Ciais; Sebastian Pokutta; Martin Brandt; Fabian Gieseke (ICML, 2024)

CLIP-Branches: Interactive Fine-Tuning for Text-Image Retrieval. - Christian Lülf; Denis Mayr Lima Martins; Marcos Antonio Vaz Salles; Yongluan Zhou; Fabian Gieseke (SIGIR, 2024)

CLIP-Branches: Interactive Fine-Tuning for Text-Image Retrieval. - Christian Lülf; Denis Mayr Lima Martins; Marcos Antonio Vaz Salles; Yongluan Zhou; Fabian Gieseke (CoRR, 2024)

Training neural networks end-to-end for hyperbox-based classification. - Denis Mayr Lima Martins; Christian Lülf; Fabian Gieseke (Neurocomputing, 2024)

Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation. - Jan Pauls; Max Zimmer; Berkant Turan; Sassan Saatchi; Philippe Ciais; Sebastian Pokutta; Fabian Gieseke (CoRR, 2025)

DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications. - Ibrahim Fayad; Max Zimmer; Martin Schwartz; Philippe Ciais; Fabian Gieseke; Gabriel Belouze; Sarah Brood; Aurélien de Truchis; Alexandre d'Aspremont (CoRR, 2025)