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ORCIDMario Michael Krell
Person information
- affiliation: University of California Berkeley, CA, USA
- affiliation (PhD 2015): University of Bremen, Germany
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Books and Theses
- 2015
[b1]Mario Michael Krell:
Generalizing, decoding, and optimizing support vector machine classification. University of Bremen, 2015, pp. 1-236
Journal Articles
- 2024
- [j9]Hatem Helal, Jesun Firoz, Jenna A. Bilbrey, Henry Sprueill, Kristina M. Herman
, Mario Michael Krell, Tom Murray, Manuel Lopez Roldan, Mike Kraus, Ang Li, Payel Das, Sotiris S. Xantheas, Sutanay Choudhury:
Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. J. Chem. Inf. Model. 64(5): 1568-1580 (2024) - 2022
- [j8]Sourabh Kulkarni, Mario Michael Krell, Seth Nabarro, Csaba Andras Moritz:
Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19. ACM J. Emerg. Technol. Comput. Syst. 18(2): 30:1-30:24 (2022) - 2017
- [j7]Mario Michael Krell, Sirko Straube:
Backtransformation: a new representation of data processing chains with a scalar decision function. Adv. Data Anal. Classif. 11(2): 415-439 (2017) - 2015
- [j6]Alexander Fabisch, Jan Hendrik Metzen, Mario Michael Krell, Frank Kirchner:
Accounting for Task-Difficulty in Active Multi-Task Robot Control Learning. Künstliche Intell. 29(4): 369-377 (2015) - [j5]Mario Michael Krell, Hendrik Wöhrle:
New one-class classifiers based on the origin separation approach. Pattern Recognit. Lett. 53: 93-99 (2015) - [j4]Hendrik Wöhrle, Mario Michael Krell, Sirko Straube, Su Kyoung Kim, Elsa Andrea Kirchner, Frank Kirchner:
An Adaptive Spatial Filter for User-Independent Single Trial Detection of Event-Related Potentials. IEEE Trans. Biomed. Eng. 62(7): 1696-1705 (2015) - 2014
- [j3]Sirko Straube, Mario Michael Krell:
How to evaluate an agent's behavior to infrequent events? - Reliable performance estimation insensitive to class distribution. Frontiers Comput. Neurosci. 8: 43 (2014) - [j2]Mario Michael Krell, David Feess, Sirko Straube:
Balanced Relative Margin Machine - The missing piece between FDA and SVM classification. Pattern Recognit. Lett. 41: 43-52 (2014) - 2013
- [j1]Mario Michael Krell, Sirko Straube, Anett Seeland, Hendrik Wöhrle, Johannes Teiwes, Jan Hendrik Metzen, Elsa Andrea Kirchner, Frank Kirchner:
pySPACE - a signal processing and classification environment in Python. Frontiers Neuroinformatics 7: 40 (2013)
Conference and Workshop Papers
- 2020
- [c9]Sourabh Kulkarni, Alexander Tsyplikhin, Mario Michael Krell, Csaba Andras Moritz:
Accelerating Simulation-based Inference with Emerging AI Hardware. ICRC 2020: 126-132 - 2017
- [c8]Mario Michael Krell, Su Kyoung Kim:
Rotational data augmentation for electroencephalographic data. EMBC 2017: 471-474 - [c7]Leif Christensen, Mario Michael Krell, Frank Kirchner:
Learning magnetic field distortion compensation for robotic systems. IROS 2017: 3516-3521 - [c6]Bilal Wehbe, Alexander Fabisch, Mario Michael Krell:
Online model identification for underwater vehicles through incremental support vector regression. IROS 2017: 4173-4180 - 2015
- [c5]Tim Tiedemann, Thomas Vögele, Mario Michael Krell, Jan Hendrik Metzen, Frank Kirchner:
Concept of a Data Thread Based Parking Space Occupancy Prediction in a Berlin Pilot Region. AAAI Workshop: AI for Transportation 2015 - [c4]Mario Michael Krell, Nils Wilshusen, Andrei Cristian Ignat, Su Kyoung Kim:
Comparison of Data Selection Strategies for Online Support Vector Machine Classification. NEUROTECHNIX 2015: 59-67 - [c3]Mario Michael Krell, Hendrik Wöhrle, Anett Seeland:
raxDAWN: Circumventing Overfitting of the Adaptive xDAWN. NEUROTECHNIX 2015: 68-75 - 2013
- [c2]Mario Michael Krell, Marc Tabie, Hendrik Wöhrle, Elsa Andrea Kirchner:
Memory and Processing Efficient Formula for Moving Variance Calculation in EEG and EMG Signal Processing. NEUROTECHNIX 2013: 41-45 - [c1]Hendrik Wöhrle, Johannes Teiwes, Mario Michael Krell, Elsa Andrea Kirchner, Frank Kirchner:
A Dataflow-based Mobile Brain Reading System on Chip with Supervised Online Calibration - For Usage without Acquisition of Training Data. NEUROTECHNIX 2013: 46-53
Informal and Other Publications
- 2022
- [i14]Mario Michael Krell, Nils Wilshusen, Anett Seeland, Su Kyoung Kim:
Classifier Transfer with Data Selection Strategies for Online Support Vector Machine Classification with Class Imbalance. CoRR abs/2208.05112 (2022) - [i13]Mario Michael Krell, Manuel Lopez Roldan, Sreenidhi Anand, Hatem Helal, Andrew William Fitzgibbon:
Tuple Packing: Efficient Batching of Small Graphs in Graph Neural Networks. CoRR abs/2209.06354 (2022) - [i12]Hatem Helal, Jesun Firoz, Jenna A. Bilbrey, Mario Michael Krell, Tom Murray, Ang Li, Sotiris S. Xantheas, Sutanay Choudhury:
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry. CoRR abs/2211.13853 (2022) - 2021
- [i11]Daniel Ma, Gerald Friedland, Mario Michael Krell:
OrigamiSet1.0: Two New Datasets for Origami Classification and Difficulty Estimation. CoRR abs/2101.05470 (2021) - [i10]Matej Kosec, Sheng Fu, Mario Michael Krell:
Packing: Towards 2x NLP BERT Acceleration. CoRR abs/2107.02027 (2021) - [i9]Edward H. Lee, Mario Michael Krell, Alexander Tsyplikhin, Victoria Rege, Errol Colak, Kristen W. Yeom:
NanoBatch DPSGD: Exploring Differentially Private learning on ImageNet with low batch sizes on the IPU. CoRR abs/2109.12191 (2021) - 2020
- [i8]Mario Michael Krell, Bilal Wehbe:
A First Step Towards Distribution Invariant Regression Metrics. CoRR abs/2009.05176 (2020) - [i7]Sourabh Kulkarni, Mario Michael Krell, Seth Nabarro, Csaba Andras Moritz:
Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19. CoRR abs/2012.14332 (2020) - 2018
- [i6]Mario Michael Krell, Anett Seeland, Su Kyoung Kim:
Data Augmentation for Brain-Computer Interfaces: Analysis on Event-Related Potentials Data. CoRR abs/1801.02730 (2018) - [i5]Mario Michael Krell:
Generalizing, Decoding, and Optimizing Support Vector Machine Classification. CoRR abs/1801.04929 (2018) - [i4]Bilal Wehbe, Octavio Arriaga, Mario Michael Krell, Frank Kirchner:
Learning of Multi-Context Models for Autonomous Underwater Vehicles. CoRR abs/1809.06179 (2018) - [i3]Gerald Friedland, Alfredo Metere, Mario Michael Krell:
A Practical Approach to Sizing Neural Networks. CoRR abs/1810.02328 (2018) - 2017
- [i2]Gerald Friedland, Mario Michael Krell:
A Capacity Scaling Law for Artificial Neural Networks. CoRR abs/1708.06019 (2017) - [i1]Mario Michael Krell, Julia Bernd, Yifan Li, Daniel Ma, Jaeyoung Choi, Michael Ellsworth, Damian Borth, Gerald Friedland:
Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Ver. CoRR abs/1712.09915 (2017)
Coauthor Index
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