:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Bourdin, Yann, Legrand, Pierrick, Roche, Fanny
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.07393
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Time-Varying Audio Effect Modeling by End-to-End Adversarial Training
by: Bourdin, Yann, et al.
Published: (2025)

Backpropagation-Free Metropolis-Adjusted Langevin Algorithm
by: Cobb, Adam D., et al.
Published: (2025)

Backpropagation Neural Tree
by: Ojha, Varun, et al.
Published: (2022)

Dynamic Spectral Backpropagation for Efficient Neural Network Training
by: Muthuraman, Mannmohan
Published: (2025)

Stabilizing Backpropagation Through Time to Learn Complex Physics
by: Schnell, Patrick, et al.
Published: (2024)

Evolutionary Algorithm for Reservoir Learning and Yielding
by: Testu, Julien, et al.
Published: (2026)

Stabilizing Backpropagation in 16-bit Neural Training with Modified Adam Optimizer
by: Yun, Juyoung
Published: (2023)

Efficient Training of Neural Fractional-Order Differential Equation via Adjoint Backpropagation
by: Kang, Qiyu, et al.
Published: (2025)

THDC: Training Hyperdimensional Computing Models with Backpropagation
by: Dejonghe, Hanne, et al.
Published: (2026)

Backpropagation Through Time For Networks With Long-Term Dependencies
by: Bird, George, et al.
Published: (2021)

Time Series Compression using Quaternion Valued Neural Networks and Quaternion Backpropagation
by: Pöppelbaum, Johannes, et al.
Published: (2024)

Phasor Memory Networks: Stable Backpropagation Through Time for Scalable Explicit Memory
by: Goo, Sungwoo, et al.
Published: (2026)

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation
by: Rivkin, Dmitriy, et al.
Published: (2026)

Truncated Matrix Completion - An Empirical Study
by: Naik, Rishhabh, et al.
Published: (2025)

Fast and Interpretable Autoregressive Estimation with Neural Network Backpropagation
by: Lucena, Anaísa, et al.
Published: (2026)

Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
by: Yu, Chengting, et al.
Published: (2024)

Advancing On-Device Neural Network Training with TinyPropv2: Dynamic, Sparse, and Efficient Backpropagation
by: Rüb, Marcus, et al.
Published: (2024)

Dense Backpropagation Improves Training for Sparse Mixture-of-Experts
by: Panda, Ashwinee, et al.
Published: (2025)

Beyond Backpropagation: Exploring Innovative Algorithms for Energy-Efficient Deep Neural Network Training
by: Spyra, Przemysław
Published: (2025)

Fine-tuning Diffusion Policies with Backpropagation Through Diffusion Timesteps
by: Yang, Ningyuan, et al.
Published: (2025)

Training Implicit Networks for Image Deblurring using Jacobian-Free Backpropagation
by: Liu, Linghai, et al.
Published: (2024)

SAL: Selective Adaptive Learning for Backpropagation-Free Training with Sparsification
by: Liu, Fanping, et al.
Published: (2026)

Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation
by: Sójka, Damian, et al.
Published: (2026)

Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory
by: Mathiasen, Alexander, et al.
Published: (2024)

The Cost of Avoiding Backpropagation
by: Panchal, Kunjal, et al.
Published: (2025)

Optimal Control Theoretic Neural Optimizer: From Backpropagation to Dynamic Programming
by: Liu, Guan-Horng, et al.
Published: (2025)

Timing-Based Backpropagation in Spiking Neural Networks Without Single-Spike Restrictions
by: Yamamoto, Kakei, et al.
Published: (2022)

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization
by: Zhang, Aozhong, et al.
Published: (2024)

FFCL: Forward-Forward Net with Cortical Loops, Training and Inference on Edge Without Backpropagation
by: Karkehabadi, Ali, et al.
Published: (2024)

Comprehensive Survey of Complex-Valued Neural Networks: Insights into Backpropagation and Activation Functions
by: Hammad, M. M.
Published: (2024)

Practical Boolean Backpropagation
by: Golbert, Simon
Published: (2025)

Neural Garbage Collection: Learning to Forget while Learning to Reason
by: Li, Michael Y., et al.
Published: (2026)

StreamBP: Memory-Efficient Exact Backpropagation for Long Sequence Training of LLMs
by: Luo, Qijun, et al.
Published: (2025)

ABPT: Amended Backpropagation through Time with Partially Differentiable Rewards
by: Li, Fanxing, et al.
Published: (2025)

Rethinking Deep Learning: Propagating Information in Neural Networks without Backpropagation and Statistical Optimization
by: Itoh, Kei
Published: (2024)

Efficient Deep Learning with Decorrelated Backpropagation
by: Dalm, Sander, et al.
Published: (2024)

Forecasting Intraday Power Output by a Set of PV Systems using Recurrent Neural Networks and Physical Covariates
by: Bruneau, Pierrick, et al.
Published: (2023)

JaxDecompiler: Redefining Gradient-Informed Software Design
by: Pochelu, Pierrick
Published: (2024)

Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
by: Ghader, Mohammadnavid, et al.
Published: (2025)

Backpropagation on Dynamical Networks
by: Tan, Eugene, et al.
Published: (2022)