Memory and Processing Efficient Formula for Moving Variance Calculation in EEG and EMG Signal Processing. - Mario Michael Krell; Marc Tabie; Hendrik Wöhrle; Elsa Andrea Kirchner (NEUROTECHNIX, 2013)

A Dataflow-based Mobile Brain Reading System on Chip with Supervised Online Calibration - For Usage without Acquisition of Training Data. - Hendrik Wöhrle; Johannes Teiwes; Mario Michael Krell; Elsa Andrea Kirchner; Frank Kirchner (NEUROTECHNIX, 2013)

pySPACE - a signal processing and classification environment in Python. - Mario Michael Krell; Sirko Straube; Anett Seeland; Hendrik Wöhrle; Johannes Teiwes; Jan Hendrik Metzen; Elsa Andrea Kirchner; Frank Kirchner (Frontiers Neuroinformatics, 2013)

How to evaluate an agent's behavior to infrequent events? - Reliable performance estimation insensitive to class distribution. - Sirko Straube; Mario Michael Krell (Frontiers Comput. Neurosci., 2014)

Balanced Relative Margin Machine - The missing piece between FDA and SVM classification. - Mario Michael Krell; David Feess; Sirko Straube (Pattern Recognit. Lett., 2014)

Concept of a Data Thread Based Parking Space Occupancy Prediction in a Berlin Pilot Region. - Tim Tiedemann; Thomas Vögele; Mario Michael Krell; Jan Hendrik Metzen; Frank Kirchner (AAAI Workshop: AI for Transportation, 2015)

Comparison of Data Selection Strategies for Online Support Vector Machine Classification. - Mario Michael Krell; Nils Wilshusen; Andrei Cristian Ignat; Su Kyoung Kim (NEUROTECHNIX, 2015)

raxDAWN: Circumventing Overfitting of the Adaptive xDAWN. - Mario Michael Krell; Hendrik Wöhrle; Anett Seeland (NEUROTECHNIX, 2015)

Accounting for Task-Difficulty in Active Multi-Task Robot Control Learning. - Alexander Fabisch; Jan Hendrik Metzen; Mario Michael Krell; Frank Kirchner (Künstliche Intell., 2015)

New one-class classifiers based on the origin separation approach. - Mario Michael Krell; Hendrik Wöhrle (Pattern Recognit. Lett., 2015)

An Adaptive Spatial Filter for User-Independent Single Trial Detection of Event-Related Potentials. - Hendrik Wöhrle; Mario Michael Krell; Sirko Straube; Su Kyoung Kim; Elsa Andrea Kirchner; Frank Kirchner (IEEE Trans. Biomed. Eng., 2015)

Generalizing, decoding, and optimizing support vector machine classification. - Mario Michael Krell (2015)

Rotational data augmentation for electroencephalographic data. - Mario Michael Krell; Su Kyoung Kim (EMBC, 2017)

Learning magnetic field distortion compensation for robotic systems. - Leif Christensen; Mario Michael Krell; Frank Kirchner (IROS, 2017)

Online model identification for underwater vehicles through incremental support vector regression. - Bilal Wehbe; Alexander Fabisch; Mario Michael Krell (IROS, 2017)

Backtransformation: a new representation of data processing chains with a scalar decision function. - Mario Michael Krell; Sirko Straube (Adv. Data Anal. Classif., 2017)

A Capacity Scaling Law for Artificial Neural Networks. - Gerald Friedland; Mario Michael Krell (CoRR, 2017)

Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Ver. - Mario Michael Krell; Julia Bernd; Yifan Li; Daniel Ma; Jaeyoung Choi 002; Michael Ellsworth; Damian Borth; Gerald Friedland (CoRR, 2017)

Data Augmentation for Brain-Computer Interfaces: Analysis on Event-Related Potentials Data. - Mario Michael Krell; Anett Seeland; Su Kyoung Kim (CoRR, 2018)

Generalizing, Decoding, and Optimizing Support Vector Machine Classification. - Mario Michael Krell (CoRR, 2018)

Learning of Multi-Context Models for Autonomous Underwater Vehicles. - Bilal Wehbe; Octavio Arriaga; Mario Michael Krell; Frank Kirchner (CoRR, 2018)

A Practical Approach to Sizing Neural Networks. - Gerald Friedland; Alfredo Metere; Mario Michael Krell (CoRR, 2018)

Accelerating Simulation-based Inference with Emerging AI Hardware. - Sourabh Kulkarni; Alexander Tsyplikhin; Mario Michael Krell; Csaba Andras Moritz (ICRC, 2020)

A First Step Towards Distribution Invariant Regression Metrics. - Mario Michael Krell; Bilal Wehbe (CoRR, 2020)

OrigamiSet1.0: Two New Datasets for Origami Classification and Difficulty Estimation. - Daniel Ma; Gerald Friedland; Mario Michael Krell (CoRR, 2021)

Packing: Towards 2x NLP BERT Acceleration. - Matej Kosec; Sheng Fu; Mario Michael Krell (CoRR, 2021)

NanoBatch DPSGD: Exploring Differentially Private learning on ImageNet with low batch sizes on the IPU. - Edward H. Lee; Mario Michael Krell; Alexander Tsyplikhin; Victoria Rege; Errol Colak; Kristen W. Yeom (CoRR, 2021)

Classifier Transfer with Data Selection Strategies for Online Support Vector Machine Classification with Class Imbalance. - Mario Michael Krell; Nils Wilshusen; Anett Seeland; Su Kyoung Kim (CoRR, 2022)

Tuple Packing: Efficient Batching of Small Graphs in Graph Neural Networks. - Mario Michael Krell; Manuel Lopez Roldan; Sreenidhi Anand; Hatem Helal; Andrew William Fitzgibbon (CoRR, 2022)

Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Mario Michael Krell; Tom Murray; Ang Li 006; Sotiris S. Xantheas; Sutanay Choudhury (CoRR, 2022)

Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19. - Sourabh Kulkarni; Mario Michael Krell; Seth Nabarro; Csaba Andras Moritz (ACM J. Emerg. Technol. Comput. Syst., 2022)

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Henry Sprueill; Kristina M. Herman; Mario Michael Krell; Tom Murray; Manuel Lopez Roldan; Mike Kraus; Ang Li 006; Payel Das; Sotiris S. Xantheas; et al. (J. Chem. Inf. Model., 2024)