Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs
Fuente:
arXiv
Saved in:
| Main Authors: | Pes, Lorenzo, Chehreghan, Maryam Dehbashizadeh, Luiken, Rick, Stuijk, Sander, Stabile, Ripalta, Corradi, Federico |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Active Dendrites Enable Efficient Continual Learning in Time-To-First-Spike Neural Networks
by: Pes, Lorenzo, et al.
Published: (2024)
by: Pes, Lorenzo, et al.
Published: (2024)
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
by: Pes, Lorenzo, et al.
Published: (2025)
by: Pes, Lorenzo, et al.
Published: (2025)
In situ fine-tuning of in silico trained Optical Neural Networks
by: Kosmella, Gianluca, et al.
Published: (2025)
by: Kosmella, Gianluca, et al.
Published: (2025)
Exploring Gain-Doped-Waveguide-Synapse for Neuromorphic Applications: A Pulsed Pump-Signal Approach
by: Otupiri, Robert, et al.
Published: (2025)
by: Otupiri, Robert, et al.
Published: (2025)
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
by: Eissa, Sherif, et al.
Published: (2025)
by: Eissa, Sherif, et al.
Published: (2025)
Spatiotemporal Radar Gesture Recognition with Hybrid Spiking Neural Networks: Balancing Accuracy and Efficiency
by: Mazzieri, Riccardo, et al.
Published: (2025)
by: Mazzieri, Riccardo, et al.
Published: (2025)
LOKI: a 0.266 pJ/SOP Digital SNN Accelerator with Multi-Cycle Clock-Gated SRAM in 22nm
by: Luiken, Rick, et al.
Published: (2025)
by: Luiken, Rick, et al.
Published: (2025)
Short-reach Optical Communications: A Real-world Task for Neuromorphic Hardware
by: Arnold, Elias, et al.
Published: (2024)
by: Arnold, Elias, et al.
Published: (2024)
A Multiplication-Free Spike-Time Learning Algorithm and its Efficient FPGA Implementation for On-Chip SNN Training
by: Mirsadeghi, Maryam, et al.
Published: (2026)
by: Mirsadeghi, Maryam, et al.
Published: (2026)
Hardware-aware training of models with synaptic delays for digital event-driven neuromorphic processors
by: Patino-Saucedo, Alberto, et al.
Published: (2024)
by: Patino-Saucedo, Alberto, et al.
Published: (2024)
Anytime Analysis on BinVal: Adaptive Parameters Help
by: Kötzing, Timo, et al.
Published: (2026)
by: Kötzing, Timo, et al.
Published: (2026)
Scalable Network Emulation on Analog Neuromorphic Hardware
by: Arnold, Elias, et al.
Published: (2024)
by: Arnold, Elias, et al.
Published: (2024)
NeoHebbian Synapses to Accelerate Online Training of Neuromorphic Hardware
by: Pande, Shubham, et al.
Published: (2024)
by: Pande, Shubham, et al.
Published: (2024)
Bridging Quantized Artificial Neural Networks and Neuromorphic Hardware
by: Chen, Zhenhui, et al.
Published: (2025)
by: Chen, Zhenhui, et al.
Published: (2025)
Demonstrating the Advantages of Analog Wafer-Scale Neuromorphic Hardware
by: Schmidt, Hartmut, et al.
Published: (2024)
by: Schmidt, Hartmut, et al.
Published: (2024)
Amortized Inference of Neuron Parameters on Analog Neuromorphic Hardware
by: Kaiser, Jakob, et al.
Published: (2026)
by: Kaiser, Jakob, et al.
Published: (2026)
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware
by: Müller, Eric, et al.
Published: (2024)
by: Müller, Eric, et al.
Published: (2024)
SpikingGamma: Surrogate-Gradient Free and Temporally Precise Online Training of Spiking Neural Networks with Smoothed Delays
by: Koopman, Roel, et al.
Published: (2026)
by: Koopman, Roel, et al.
Published: (2026)
Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System
by: Max, Kevin, et al.
Published: (2025)
by: Max, Kevin, et al.
Published: (2025)
Hardware-Aware Model Design and Training of Silicon-based Analog Neural Networks
by: Filippeschi, Giulio, et al.
Published: (2025)
by: Filippeschi, Giulio, et al.
Published: (2025)
Finger Force Decoding from Motor Units Activity on Neuromorphic Hardware
by: Baracat, Farah, et al.
Published: (2025)
by: Baracat, Farah, et al.
Published: (2025)
Analysis of Generalized Hebbian Learning Algorithm for Neuromorphic Hardware Using Spinnaker
by: Sharma, Shivani, et al.
Published: (2024)
by: Sharma, Shivani, et al.
Published: (2024)
CMOS Implementation of Field Programmable Spiking Neural Network for Hardware Reservoir Computing
by: Duran, Ckristian, et al.
Published: (2025)
by: Duran, Ckristian, et al.
Published: (2025)
hxtorch: PyTorch for BrainScaleS-2 -- Perceptrons on Analog Neuromorphic Hardware
by: Spilger, Philipp, et al.
Published: (2020)
by: Spilger, Philipp, et al.
Published: (2020)
Oscillator-Based Associative Memory with Exponential Capacity: Theory, Algorithms, and Hardware Implementation
by: Ogranovich, Arie, et al.
Published: (2026)
by: Ogranovich, Arie, et al.
Published: (2026)
Analysis of Search Heuristics in the Multi-Armed Bandit Setting
by: Brandt, Jasmin, et al.
Published: (2026)
by: Brandt, Jasmin, et al.
Published: (2026)
Fine-Tuning Surrogate Gradient Learning for Optimal Hardware Performance in Spiking Neural Networks
by: Aliyev, Ilkin, et al.
Published: (2024)
by: Aliyev, Ilkin, et al.
Published: (2024)
$SpikePack$: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility
by: Shen, Guobin, et al.
Published: (2025)
by: Shen, Guobin, et al.
Published: (2025)
Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning
by: Li, Ke, et al.
Published: (2024)
by: Li, Ke, et al.
Published: (2024)
Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology
by: Nimbekar, Anagha, et al.
Published: (2024)
by: Nimbekar, Anagha, et al.
Published: (2024)
Loop-Extrusion Linkage: Spectral Ordering and Interval-Based Structure Discovery for Continuous Optimization
by: Unlu, Eren
Published: (2026)
by: Unlu, Eren
Published: (2026)
Synchronized Stepwise Control of Firing and Learning Thresholds in a Spiking Randomly Connected Neural Network toward Hardware Implementation
by: Nomura, Kumiko, et al.
Published: (2024)
by: Nomura, Kumiko, et al.
Published: (2024)
A Perturbation and Speciation-Based Algorithm for Dynamic Optimization Uninformed of Change
by: Signorelli, Federico, et al.
Published: (2025)
by: Signorelli, Federico, et al.
Published: (2025)
The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents
by: Pigozzi, Federico, et al.
Published: (2026)
by: Pigozzi, Federico, et al.
Published: (2026)
Fast Exploration of the Impact of Precision Reduction on Spiking Neural Networks
by: Saeedi, Sepide, et al.
Published: (2022)
by: Saeedi, Sepide, et al.
Published: (2022)
Optimal feature rescaling in machine learning based on neural networks
by: Vitrò, Federico Maria, et al.
Published: (2024)
by: Vitrò, Federico Maria, et al.
Published: (2024)
TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
by: Lee, Donghyun, et al.
Published: (2024)
by: Lee, Donghyun, et al.
Published: (2024)
Hardware-Algorithm Re-engineering of Retinal Circuit for Intelligent Object Motion Segmentation
by: Sinaga, Jason, et al.
Published: (2024)
by: Sinaga, Jason, et al.
Published: (2024)
Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
by: Ramachandran, Akshat, et al.
Published: (2024)
by: Ramachandran, Akshat, et al.
Published: (2024)
Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection
by: Wang, Shenqi, et al.
Published: (2025)
by: Wang, Shenqi, et al.
Published: (2025)
Similar Items
-
Active Dendrites Enable Efficient Continual Learning in Time-To-First-Spike Neural Networks
by: Pes, Lorenzo, et al.
Published: (2024) -
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
by: Pes, Lorenzo, et al.
Published: (2025) -
In situ fine-tuning of in silico trained Optical Neural Networks
by: Kosmella, Gianluca, et al.
Published: (2025) -
Exploring Gain-Doped-Waveguide-Synapse for Neuromorphic Applications: A Pulsed Pump-Signal Approach
by: Otupiri, Robert, et al.
Published: (2025) -
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
by: Eissa, Sherif, et al.
Published: (2025)