Richard Gerum

According to our database, Richard Gerum authored at least 13 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deep learning based decoding of single local field potential events.

Achim Schilling, Richard Gerum, Claudia Boehm, Jwan Rasheed, Claus Metzner, Andreas Maier, Caroline Reindl, Hajo M. Hamer, Patrick Krauss

NeuroImage, 2024

2023

Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology.

Richard Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer.

Cassidy Pirlot, Richard C. Gerum, Cory Efird, Joel Zylberberg, Alona Fyshe

CoRR, 2022

Different Spectral Representations in Optimized Artificial Neural Networks and Brains.

Richard C. Gerum, Cassidy Pirlot, Alona Fyshe, Joel Zylberberg

CoRR, 2022

Predictive Coding and Stochastic Resonance: Towards a Unified Theory of Auditory (Phantom) Perception.

Achim Schilling, William Sedley, Richard Gerum, Claus Metzner, Konstantin Tziridis, Andreas K. Maier, Holger Schulze, Fan-Gang Zeng, Karl J. Friston, Patrick Krauss

CoRR, 2022

2021

Quantifying the separability of data classes in neural networks.

Achim Schilling, Andreas Maier, Richard Gerum, Claus Metzner, Patrick Krauss

Neural Networks, 2021

Integration of Leaky-Integrate-and-Fire Neurons in Standard Machine Learning Architectures to Generate Hybrid Networks: A Surrogate Gradient Approach.

Richard C. Gerum, Achim Schilling

Neural Comput., 2021

2020

Sparsity through evolutionary pruning prevents neuronal networks from overfitting.

Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling

Neural Networks, 2020

pylustrator: code generation for reproducible figures for publication.

Richard Gerum

J. Open Source Softw., 2020

Spiking Machine Intelligence: What we can learn from biology and how spiking Neural Networks can help to improve Machine Learning.

Richard C. Gerum, Achim Schilling

CoRR, 2020

2019

CameraTransform: A Python package for perspective corrections and image mapping.

Richard C. Gerum, Sebastian Richter, Alexander Winterl, Christoph Mark, Ben Fabry, Céline Le Bohec, Daniel P. Zitterbart

SoftwareX, 2019

2018

How deep is deep enough? - Optimizing deep neural network architecture.

Achim Schilling, Jonas Rietsch, Richard Gerum, Holger Schulze, Claus Metzner, Patrick Krauss

CoRR, 2018

2017

CameraTransform: a Scientific Python Package for Perspective Camera Corrections.

Richard Gerum, Sebastian Richter, Alexander Winterl, Ben Fabry, Daniel P. Zitterbart

CoRR, 2017