Julian Göltz

Orcid: 0000-0002-5378-932X

According to our database1, Julian Göltz authored at least 9 papers between 2019 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Gradient-based methods for spiking physical systems.
CoRR, 2023

2022
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware.
CoRR, 2022

The Yin-Yang dataset.
Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022

2021
Fast and energy-efficient neuromorphic deep learning with first-spike times.
Nat. Mach. Intell., 2021

Fast and Energy-efficient Deep Neuromorphic Learning.
ERCIM News, 2021

2020
Fast and deep neuromorphic learning with first-spike coding.
Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020



2019
Fast and deep neuromorphic learning with time-to-first-spike coding.
CoRR, 2019


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