SNN Architecture for Differential Time Encoding Using Decoupled Processing Time. - Daniel Windhager; Bernhard Alois Moser; Michael Lunglmayr (AICAS, 2024)

Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance. - Daniel Windhager; Bernhard Moser 001; Michael Lunglmayr (EUROCAST (2), 2024)

Soil analysis with machine-learning-based processing of stepped-frequency GPR field measurements: Preliminary study. - Chunlei Xu; Michael Pregesbauer; Naga Sravani Chilukuri; Daniel Windhager; Mahsa Yousefi; Pedro Julián; Lothar Ratschbacher (CoRR, 2024)

Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding. - Daniel Windhager; Lothar Ratschbacher; Bernhard A. Moser; Michael Lunglmayr (ISCAS, 2025)

Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding. - Daniel Windhager; Lothar Ratschbacher; Bernhard Moser 001; Michael Lunglmayr (CoRR, 2025)

Lightweight LIF-only SNN accelerator using differential time encoding. - Daniel Windhager; Lothar Ratschbacher; Bernhard Alois Moser; Michael Lunglmayr (CoRR, 2025)