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ORCIDHeiko Hoffmann
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2020 – today
- 2025
[i9]Heiko Hoffmann, Richard Hoffmann:
Object-Pose Estimation With Neural Population Codes. CoRR abs/2502.13403 (2025)- 2024
- [j9]Heiko Hoffmann:
Computational model of layer 2/3 in mouse primary visual cortex explains observed visuomotor mismatch response. J. Comput. Neurosci. 52(4): 323-329 (2024) - [i8]Heiko Hoffmann:
Advantages of Neural Population Coding for Deep Learning. CoRR abs/2411.00393 (2024) - 2022
- [c16]Joseph F. Comer, Philip L. Jacobson, Heiko Hoffmann
:
Few-Shot Image Classification Along Sparse Graphs. CVPR Workshops 2022: 4186-4194 - 2021
- [c15]Soheil Kolouri, Navid Naderializadeh, Gustavo K. Rohde, Heiko Hoffmann:
Wasserstein Embedding for Graph Learning. ICLR 2021 - [c14]Navid Naderializadeh, Joseph F. Comer, Reed W. Andrews, Heiko Hoffmann, Soheil Kolouri:
Pooling by Sliced-Wasserstein Embedding. NeurIPS 2021: 3389-3400 - [i7]Navid Naderializadeh, Soheil Kolouri, Joseph F. Comer, Reed W. Andrews, Heiko Hoffmann:
Set Representation Learning with Generalized Sliced-Wasserstein Embeddings. CoRR abs/2103.03892 (2021) - [i6]Joseph F. Comer, Philip L. Jacobson, Heiko Hoffmann:
Few-Shot Image Classification Along Sparse Graphs. CoRR abs/2112.03951 (2021) - 2020
- [c13]Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash, Heiko Hoffmann:
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs. CVPR 2020: 298-307 - [i5]Heiko Hoffmann, Anne Wald:
On parameter identification problems for elliptic boundary value problems in divergence form, Part I: An abstract framework. CoRR abs/2002.05009 (2020) - [i4]Soheil Kolouri, Navid Naderializadeh, Gustavo K. Rohde, Heiko Hoffmann:
Wasserstein Embedding for Graph Learning. CoRR abs/2006.09430 (2020)
2010 – 2019
- 2019
- [j8]Heiko Hoffmann:
Sparse Associative Memory. Neural Comput. 31(5): 998-1014 (2019) - [c12]Phillip E. Pope, Soheil Kolouri, Mohammad Rostami, Charles E. Martin, Heiko Hoffmann:
Explainability Methods for Graph Convolutional Neural Networks. CVPR 2019: 10772-10781 - [i3]Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash, Heiko Hoffmann:
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs. CoRR abs/1906.10842 (2019) - 2018
- [c11]Soheil Kolouri, Gustavo K. Rohde, Heiko Hoffmann:
Sliced Wasserstein Distance for Learning Gaussian Mixture Models. CVPR 2018: 3427-3436 - [i2]Phillip E. Pope, Soheil Kolouri, Mohammad Rostami, Charles E. Martin, Heiko Hoffmann:
Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks. CoRR abs/1812.00265 (2018) - 2017
- [c10]Soheil Kolouri, Charles E. Martin, Heiko Hoffmann:
Explaining Distributed Neural Activations via Unsupervised Learning. CVPR Workshops 2017: 1670-1678 - [i1]Soheil Kolouri, Gustavo K. Rohde, Heiko Hoffmann:
Sliced Wasserstein Distance for Learning Gaussian Mixture Models. CoRR abs/1711.05376 (2017) - 2014
- [j7]Heiko Hoffmann, Zhichao Chen, Darren Earl, Derek Mitchell, Behnam Salemi, Jivko Sinapov:
Adaptive robotic tool use under variable grasps. Robotics Auton. Syst. 62(6): 833-846 (2014) - [c9]Charles E. Martin, Heiko Hoffmann:
Fast re-learning of a controller from sparse data. SMC 2014: 973-978 - 2013
- [j6]Auke Jan Ijspeert, Jun Nakanishi, Heiko Hoffmann, Peter Pastor, Stefan Schaal:
Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors. Neural Comput. 25(2): 328-373 (2013) - 2011
- [c8]M. Anthony Lewis, Matthew R. Bunting, Behnam Salemi, Heiko Hoffmann:
Toward Ultra High Speed Locomotors: Design and test of a cheetah robot hind limb. ICRA 2011: 1990-1996 - [c7]Heiko Hoffmann, Michael D. Howard, Michael J. Daily:
Fast pattern matching with time-delay neural networks. IJCNN 2011: 2424-2429
2000 – 2009
- 2009
- [j5]Heiko Hoffmann, Stefan Schaal, Sethu Vijayakumar:
Local Dimensionality Reduction for Non-Parametric Regression. Neural Process. Lett. 29(2): 109-131 (2009) - [c6]Peter Pastor, Heiko Hoffmann, Tamim Asfour, Stefan Schaal:
Learning and generalization of motor skills by learning from demonstration. ICRA 2009: 763-768 - [c5]Heiko Hoffmann, Peter Pastor, Dae-Hyung Park, Stefan Schaal:
Biologically-inspired dynamical systems for movement generation: Automatic real-time goal adaptation and obstacle avoidance. ICRA 2009: 2587-2592 - 2008
- [c4]Gunter Teichmann, Heiko Hoffmann, Martin Engelien, Elke Eichenberg, Diana Ruth:
Software on Demand (SWoD) 2.0 - Bedarfsgerechte Software für die Zusammenarbeit in Business Communities. GeNeMe 2008: 111-122 - [c3]Dae-Hyung Park, Heiko Hoffmann, Peter Pastor, Stefan Schaal:
Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields. Humanoids 2008: 91-98 - 2007
- [j4]Heiko Hoffmann:
Perception through visuomotor anticipation in a mobile robot. Neural Networks 20(1): 22-33 (2007) - [j3]Heiko Hoffmann:
Kernel PCA for novelty detection. Pattern Recognit. 40(3): 863-874 (2007) - [c2]Heiko Hoffmann, Georgios Petkos, Sebastian Bitzer, Sethu Vijayakumar:
Sensor-assisted adaptive motor control under continuously varying context. ICINCO-ICSO 2007: 262-269 - 2005
- [b1]Heiko Hoffmann:
Unsupervised learning of visuomotor associations. Bielefeld University, 2005, ISBN 3-8325-0858-9, pp. 1-188 - [j2]Heiko Hoffmann, Wolfram Schenck, Ralf Möller:
Learning visuomotor transformations for gaze-control and grasping. Biol. Cybern. 93(2): 119-130 (2005) - 2004
- [j1]Ralf Möller, Heiko Hoffmann:
An extension of neural gas to local PCA. Neurocomputing 62: 305-326 (2004) - 2003
- [c1]Heiko Hoffmann, Ralf Möller:
Unsupervised Learning of a Kinematic Arm Model. ICANN 2003: 463-470
Coauthor Index
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