Michael Hersche

Orcid: 0000-0003-3065-7639

According to our database1, Michael Hersche authored at least 32 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures.
CoRR, 2024

Terminating Differentiable Tree Experts.
Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

Towards Learning Abductive Reasoning Using VSA Distributed Representations.
Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

12 mJ Per Class On-Device Online Few-Shot Class-Incremental Learning.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

Zero-Shot Classification Using Hyperdimensional Computing.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023
A neuro-vector-symbolic architecture for solving Raven's progressive matrices.
Nat. Mac. Intell., April, 2023

Raw data related to In-memory factorization of holographic perceptual representations.
Dataset, February, 2023

Few-Shot Continual Learning Based on Vector Symbolic Architectures.
Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Neuro-vector-symbolic architectures: Exploring computation in superposition for perception, reasoning, and combinatorial search.
PhD thesis, 2023

TCNCA: Temporal Convolution Network with Chunked Attention for Scalable Sequence Processing.
CoRR, 2023

Factorizers for Distributed Sparse Block Codes.
CoRR, 2023

MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Solving Raven's Progressive Matrices via a Neuro-vector-symbolic Architecture.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Decoding Superpositions of Bound Symbols Represented by Distributed Representations.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

VSA-based Positional Encoding Can Replace Recurrent Networks in Emergent Symbol Binding.
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

2022
In-memory factorization of holographic perceptual representations.
CoRR, 2022

In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory.
Proceedings of the 48th IEEE European Solid State Circuits Conference, 2022

Constrained Few-shot Class-incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Energy Efficient In-Memory Hyperdimensional Encoding for Spatio-Temporal Signal Processing.
IEEE Trans. Circuits Syst. II Express Briefs, 2021

Near-channel classifier: symbiotic communication and classification in high-dimensional space.
Brain Informatics, 2021

Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain-Machine Interfaces.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network.
Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021

2020
Binarization Methods for Motor-Imagery Brain-Computer Interface Classification.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2020

EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces.
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Q-EEGNet: an Energy-Efficient 8-bit Quantized Parallel EEGNet Implementation for Edge Motor-Imagery Brain-Machine Interfaces.
Proceedings of the IEEE International Conference on Smart Computing, 2020

An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing.
Proceedings of the 2020 IEEE International Symposium on Medical Measurements and Applications, 2020

Integrating event-based dynamic vision sensors with sparse hyperdimensional computing: a low-power accelerator with online learning capability.
Proceedings of the ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design, 2020

Compressing Subject-specific Brain-Computer Interface Models into One Model by Superposition in Hyperdimensional Space.
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Evolvable Hyperdimensional Computing: Unsupervised Regeneration of Associative Memory to Recover Faulty Components.
Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

Binary Models for Motor-Imagery Brain-Computer Interfaces: Sparse Random Projection and Binarized SVM.
Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2018
Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer Interfaces.
CoRR, 2018

Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features.
Proceedings of the 26th European Signal Processing Conference, 2018


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