Cover Image

StochEP: Stochastic Equilibrium Propagation for Spiking Convergent Recurrent Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Jiaqi, Jiang, Yi, Sengupta, Abhronil
Format:	Preprint
Published:	2025
Subjects:	Emerging Technologies Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs
by: Lin, Jiaqi, et al.
Published: (2025)

Spatio-Temporal Pruning for Compressed Spiking Large Language Models
by: Jiang, Yi, et al.
Published: (2025)

Exploring the Potential of Spiking Neural Networks in UWB Channel Estimation
by: Zhang, Youdong, et al.
Published: (2025)

RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers
by: Mia, Md Zesun Ahmed, et al.
Published: (2026)

Delving Deeper Into Astromorphic Transformers
by: Mia, Md Zesun Ahmed, et al.
Published: (2023)

Learning Dynamics in Memristor-Based Equilibrium Propagation
by: Döll, Michael, et al.
Published: (2025)

Transductive Spiking Graph Neural Networks for Loihi
by: Snyder, Shay, et al.
Published: (2024)

Variation-Resilient FeFET-Based In-Memory Computing Leveraging Probabilistic Deep Learning
by: Manna, Bibhas, et al.
Published: (2023)

Fully Analog Resonant Recurrent Neural Network via Metacircuit
by: Zhou, Zixin, et al.
Published: (2026)

Unleashing the Expressive Power of Pulse-Based Quantum Neural Networks
by: Tao, Han-Xiao, et al.
Published: (2024)

On Optimizing Hyperparameters for Quantum Neural Networks
by: Herbst, Sabrina, et al.
Published: (2024)

Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale
by: Ahmed, Soyed Tuhin, et al.
Published: (2023)

Enhancing Reliability of Neural Networks at the Edge: Inverted Normalization with Stochastic Affine Transformations
by: Ahmed, Soyed Tuhin, et al.
Published: (2024)

Analyzing Images of Blood Cells with Quantum Machine Learning Methods: Equilibrium Propagation and Variational Quantum Circuits to Detect Acute Myeloid Leukemia
by: Bano, A., et al.
Published: (2026)

Hardware in Loop Learning with Spin Stochastic Neurons
by: Islam, A N M Nafiul, et al.
Published: (2023)

Dependence of Equilibrium Propagation Training Success on Network Architecture
by: Wang, Qingshan, et al.
Published: (2026)

On the Adversarial Robustness of Spiking Neural Networks Trained by Local Learning
by: Lin, Jiaqi, et al.
Published: (2025)

Thermodynamics-Inspired Computing with Oscillatory Neural Networks for Inverse Matrix Computation
by: Tsormpatzoglou, George, et al.
Published: (2025)

Neural CRNs: A Natural Implementation of Learning in Chemical Reaction Networks
by: Nagipogu, Rajiv Teja, et al.
Published: (2024)

Device Modeling Bias in ReRAM-based Neural Network Simulations
by: Yousuf, Osama, et al.
Published: (2022)

Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity
by: Katti, Prabodh, et al.
Published: (2023)

Clustering Guided Residual Neural Networks for Multi-Tx Localization in Molecular Communications
by: Sonmez, Ali, et al.
Published: (2025)

Performance Analysis of Convolutional Neural Network By Applying Unconstrained Binary Quadratic Programming
by: Sharma, Aasish Kumar, et al.
Published: (2025)

Hardware-Efficient Photonic Tensor Core: Accelerating Deep Neural Networks with Structured Compression
by: Ning, Shupeng, et al.
Published: (2025)

Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer
by: Pelke, Rebecca, et al.
Published: (2025)

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference
by: Gallo, Manuel Le, et al.
Published: (2023)

High Convergence Rates of CMOS Invertible Logic Circuits Based on Many-Body Hamiltonians
by: Onizawa, Naoya, et al.
Published: (2026)

Neuromorphic Cybersecurity with Semi-supervised Lifelong Learning
by: Mia, Md Zesun Ahmed, et al.
Published: (2025)

Stoch-IMC: A Bit-Parallel Stochastic In-Memory Computing Architecture Based on STT-MRAM
by: Hajisadeghi, Amir M., et al.
Published: (2024)

Enhanced Convergence in p-bit Based Simulated Annealing with Partial Deactivation for Large-Scale Combinatorial Optimization Problems
by: Onizawa, Naoya, et al.
Published: (2026)

Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise
by: Yang, Xiaoxuan, et al.
Published: (2021)

Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks
by: Dequino, Alberto, et al.
Published: (2024)

M3ICRO: Machine Learning-Enabled Compact Photonic Tensor Core based on PRogrammable Multi-Operand Multimode Interference
by: Gu, Jiaqi, et al.
Published: (2023)

Hybrid Quantum Neural Networks for Efficient Protein-Ligand Binding Affinity Prediction
by: Jeong, Seon-Geun, et al.
Published: (2025)

BitLogic: Training Framework for Gradient-Based FPGA-Native Neural Networks
by: Bührer, Simon, et al.
Published: (2026)

Multi-Objective Neural Architecture Search for In-Memory Computing
by: Amin, Md Hasibul, et al.
Published: (2024)

Interpretability as Alignment: Making Internal Understanding a Design Principle
by: Sengupta, Aadit, et al.
Published: (2025)

Perfecting Imperfect Physical Neural Networks with Transferable Robustness using Sharpness-Aware Training
by: Xu, Tengji, et al.
Published: (2024)

Machine Intelligence on Wireless Edge Networks
by: Vadlamani, Sri Krishna, et al.
Published: (2025)

Joint Masked Reconstruction and Contrastive Learning for Mining Interactions Between Proteins
by: Li, Jiang, et al.
Published: (2025)