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Tomas Hrycej
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2020 – today
- 2024
- [i7]Bernhard Bermeitinger, Tomas Hrycej, Massimo Pavone, Julianus Kath, Siegfried Handschuh:
Reducing the Transformer Architecture to a Minimum. CoRR abs/2410.13732 (2024) - [i6]Jan Frederic Spörer, Bernhard Bermeitinger, Tomas Hrycej, Niklas Limacher, Siegfried Handschuh:
Efficient Neural Network Training via Subset Pretraining. CoRR abs/2410.16523 (2024) - 2023
- [c24]Bernhard Bermeitinger
, Tomas Hrycej, Siegfried Handschuh:
Make Deep Networks Shallow Again. KDIR 2023: 339-346 - [i5]Bernhard Bermeitinger
Make Deep Networks Shallow Again. CoRR abs/2309.08414 (2023) - 2022
- [c23]Tomas Hrycej, Bernhard Bermeitinger
Training Neural Networks in Single vs. Double Precision. KDIR 2022: 307-314 - [c22]Tomas Hrycej, Bernhard Bermeitinger
Number of Attention Heads vs. Number of Transformer-encoders in Computer Vision. KDIR 2022: 315-321 - [i4]Tomas Hrycej, Bernhard Bermeitinger
Training Neural Networks in Single vs Double Precision. CoRR abs/2209.07219 (2022) - [i3]Tomas Hrycej, Bernhard Bermeitinger
Number of Attention Heads vs Number of Transformer-Encoders in Computer Vision. CoRR abs/2209.07221 (2022)
2010 – 2019
- 2019
- [c21]Bernhard Bermeitinger
Representational Capacity of Deep Neural Networks: A Computing Study. KDIR 2019: 532-538 - [c20]Bernhard Bermeitinger
Singular Value Decomposition and Neural Networks. ICANN (2) 2019: 153-164 - [i2]Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh:
Singular Value Decomposition and Neural Networks. CoRR abs/1906.11755 (2019) - [i1]Bernhard Bermeitinger, Tomas Hrycej, Siegfried Handschuh:
Representational Capacity of Deep Neural Networks - A Computing Study. CoRR abs/1907.08475 (2019)
2000 – 2009
- 2008
- [p1]Tomas Hrycej, Christian Manuel Strobel:
Extraction of Maximum Support Rules for the Root Cause Analysis. Computational Intelligence in Automotive Applications 2008: 89-99 - 2007
- [c19]Christian Manuel Strobel, Tomas Hrycej:
Root Cause Analysis for Quality Management. GfKl 2007: 405-412 - [c18]Tomas Hrycej, Matthias Grabert:
Warranty Cost Forecast Based on Car Failure Data. IJCNN 2007: 108-113 - 2006
- [j7]Rafael Schmidt, Tomas Hrycej, Eric Stützle:
Multivariate distribution models with generalized hyperbolic margins. Comput. Stat. Data Anal. 50(8): 2065-2096 (2006) - [c17]Christian Manuel Strobel, Tomas Hrycej:
A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry. PKDD 2006: 625-632 - 2005
- [j6]Eric A. Sützle, Tomas Hrycej:
Numerical method for estimating multivariate conditional distributions. Comput. Stat. 20(1): 151-176 (2005) - 2004
- [c16]Tomas Hrycej, Jochen Hipp:
Outlier Detection by Rareness Assumption. GI Jahrestagung (1) 2004: 244-248 - [c15]Matthias Grabert, Markus Prechtel, Tomas Hrycej, Winfried Günther:
An Early Warning System for Vehicle Related Quality Data. ICDM 2004: 88-95 - 2002
- [c14]Eric A. Stützle, Tomas Hrycej:
Estimating Multivariate Conditional Distributions - An Application to the Truck Sales Forecast. OR 2002: 492-497 - 2001
- [j5]Tomas Hrycej:
Estimates of average complexity of neurocontrol algorithms. Neural Networks 14(8): 1089-1098 (2001) - 2000
- [c13]Tomas Hrycej:
An Estimate of the Number of Samples to Convergence for Critic Algorithms. IJCNN (3) 2000: 227-232 - [c12]Wilm Eggert, Tomas Hrycej:
Logit Demand Function with Embedded Neural Network Based Utility Function. IJCNN (5) 2000: 285-290
1990 – 1999
- 1997
- [c11]Tomas Hrycej:
Error measure for identifying chaotic attractors. ESANN 1997 - [c10]Tomas Hrycej:
Global and local optimization in adaptive neurocontrol. ICNN 1997: 848-853 - 1995
- [c9]Tomas Hrycej:
Stability and equilibrium points in neurocontrol. ICNN 1995: 617-621 - [c8]Tomas Hrycej:
Identifying chaotic attractors with neural networks. ICNN 1995: 2664-2668 - 1993
- [b2]Tomas Hrycej:
Methods for decomposition of learning in neural networks. University of Ulm, Germany, 1993, pp. 1-147 - [j4]Tomas Hrycej:
A Temporal Extension of Prolog. J. Log. Program. 15(1&2): 113-145 (1993) - 1992
- [b1]Tomas Hrycej:
Modular learning in neural networks - a modularized approach to neural network classification. Sixth-Generation computer technology series, Wiley 1992, ISBN 978-0-471-57154-4, pp. I-XIII, 1-235 - [j3]Tomas Hrycej:
Supporting supervised learning by self-organization. Neurocomputing 4(1): 17-30 (1992) - 1990
- [j2]Tomas Hrycej:
Gibbs Sampling in Bayesian Networks. Artif. Intell. 46(3): 351-363 (1990) - [c7]Tomas Hrycej:
Self-organization by delta rule. IJCNN 1990: 307-312 - [c6]Tomas Hrycej:
A modular architecture for efficient learning. IJCNN 1990: 557-562
1980 – 1989
- 1989
- [c5]Tomas Hrycej:
Unsupervised Learning by Backward Inhibition. IJCAI 1989: 170-175 - 1988
- [c4]Tomas Hrycej:
Temporal Prolog. ECAI 1988: 296-301 - [c3]Tomas Hrycej:
Intelligent Backtracking with Structured Contexts. ECAI 1988: 589-594 - 1987
- [j1]Tomas Hrycej:
A knowledge-based problem-specific program generator. ACM SIGPLAN Notices 22(2): 53-61 (1987) - [c2]Tomas Hrycej:
An Efficient Algorithm for Reasoning about Time Intervals. Expertensysteme 1987: 327-340 - 1986
- [c1]Tomas Hrycej:
Transitivity in Relations between Time Intervals. Wissensarten und ihre Darstellung 1986: 272-292
Coauthor Index
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last updated on 2024-11-28 20:34 CET by the dblp team
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