Image de couverture de livre

Deep learning for pedestrians: backpropagation in Transformers

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Boué, Laurent
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Training all-mechanical neural networks for task learning through in situ backpropagation
par: Li, Shuaifeng, et autres
Publié: (2024)

Local learning for stable backpropagation-free neural network training towards physical learning
par: Guo, Yaqi, et autres
Publié: (2026)

Training Hamiltonian neural networks without backpropagation
par: Rahma, Atamert, et autres
Publié: (2024)

Training neural networks with end-to-end optical backpropagation
par: Spall, James, et autres
Publié: (2023)

XConv: Low-memory stochastic backpropagation for convolutional layers
par: Thatipelli, Anirudh, et autres
Publié: (2021)

On quantum backpropagation, information reuse, and cheating measurement collapse
par: Abbas, Amira, et autres
Publié: (2023)

On the relationship between predictive coding and backpropagation
par: Rosenbaum, Robert
Publié: (2021)

Neural operators struggle to learn complex PDEs in pedestrian mobility: Hughes model case study
par: Chauhan, Prajwal, et autres
Publié: (2025)

An experimental comparative study of backpropagation and alternatives for training binary neural networks for image classification
par: Crulis, Ben, et autres
Publié: (2024)

Rethinking Deep Learning: Non-backpropagation and Non-optimization Machine Learning Approach Using Hebbian Neural Networks
par: Itoh, Kei
Publié: (2024)

High Significant Fault Detection in Azure Core Workload Insights
par: Lohia, Pranay, et autres
Publié: (2024)

SUS backprop: linear backpropagation algorithm for long inputs in transformers
par: Pankov, Sergey, et autres
Publié: (2025)

Self-attention as an attractor network: transient memories without backpropagation
par: D'Amico, Francesco, et autres
Publié: (2024)

One-shot backpropagation for multi-step prediction in physics-based system identification -- EXTENDED VERSION
par: Donati, Cesare, et autres
Publié: (2023)

Multi-agent reinforcement learning using echo-state network and its application to pedestrian dynamics
par: Komatsu, Hisato
Publié: (2023)

4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models
par: Solvik, Kylen, et autres
Publié: (2024)

Interpretable and backpropagation-free Green Learning for efficient multi-task echocardiographic segmentation and classification
par: Kao, Jyun-Ping, et autres
Publié: (2026)

Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule
par: Fan, Xinhao, et autres
Publié: (2024)

A case study of Generative AI in MSX Sales Copilot: Improving seller productivity with a real-time question-answering system for content recommendation
par: Singh, Manpreet, et autres
Publié: (2024)

Transformers learn factored representations
par: Shai, Adam, et autres
Publié: (2026)

Searching, fast and slow, through product catalogs
par: Ubrangala, Dayananda, et autres
Publié: (2024)

Transformer learns the cross-task prior and regularization for in-context learning
par: Lu, Fei, et autres
Publié: (2025)

Meta-learning of shared linear representations beyond well-specified linear regression
par: Even, Mathieu, et autres
Publié: (2025)

Clustering in Deep Stochastic Transformers
par: Fedorov, Lev, et autres
Publié: (2026)

Deep Kernel Fusion for Transformers
par: Zhang, Zixi, et autres
Publié: (2026)

Deep Reinforcement Learning with Swin Transformers
par: Meng, Li, et autres
Publié: (2022)

LACTOSE: Linear Array of Conditions, TOpologies with Separated Error-backpropagation -- The Differentiable "IF" Conditional for Differentiable Digital Signal Processing
par: Clarke, Christopher Johann
Publié: (2025)

In-Context Deep Learning via Transformer Models
par: Wu, Weimin, et autres
Publié: (2024)

Fine-grained large-scale content recommendations for MSX sellers
par: Singh, Manpreet, et autres
Publié: (2024)

GLIP: Electromagnetic Field Exposure Map Completion by Deep Generative Networks
par: Mallik, Mohammed, et autres
Publié: (2024)

Adaptive collaboration for online personalized distributed learning with heterogeneous clients
par: Philippenko, Constantin, et autres
Publié: (2025)

Deep Double Q-learning
par: Nagarajan, Prabhat, et autres
Publié: (2025)

Uncertainty Propagation in the Fast Fourier Transform
par: Schmid, Luca, et autres
Publié: (2025)

DeepCrossAttention: Supercharging Transformer Residual Connections
par: Heddes, Mike, et autres
Publié: (2025)

Spectrum-Adaptive Generalization Bounds for Trained Deep Transformers
par: Sakai, Mana, et autres
Publié: (2026)

Deep conditional distribution learning via conditional Föllmer flow
par: Chang, Jinyuan, et autres
Publié: (2024)

Deep Manifold Transformation for Protein Representation Learning
par: Hu, Bozhen, et autres
Publié: (2024)

Self-supervised learning for phase retrieval
par: Sechaud, Victor, et autres
Publié: (2025)

Verified Lifting of Deep learning Operators
par: Zhan, Qi, et autres
Publié: (2024)

Deep learning and the rate of approximation by flows
par: Cheng, Jingpu, et autres
Publié: (2026)