Novel Saliency Analysis for the Forward Forward Algorithm
Fuente:
arXiv
Saved in:
| Main Author: | Bakhshi, Mitra |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Reshaping the Forward-Forward Algorithm with a Similarity-Based Objective
by: Gong, James, et al.
Published: (2025)
by: Gong, James, et al.
Published: (2025)
Employing Layerwised Unsupervised Learning to Lessen Data and Loss Requirements in Forward-Forward Algorithms
by: Hwang, Taewook, et al.
Published: (2024)
by: Hwang, Taewook, et al.
Published: (2024)
Hyperspherical Forward-Forward with Prototypical Representations
by: Sarode, Shalini, et al.
Published: (2026)
by: Sarode, Shalini, et al.
Published: (2026)
Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
by: Ghader, Mohammadnavid, et al.
Published: (2025)
by: Ghader, Mohammadnavid, et al.
Published: (2025)
Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm
by: Papachristodoulou, Andreas, et al.
Published: (2023)
by: Papachristodoulou, Andreas, et al.
Published: (2023)
Adaptive Multi-Scale Goodness Aggregation for Forward-Forward Learning
by: Beigzad, Salar, et al.
Published: (2026)
by: Beigzad, Salar, et al.
Published: (2026)
Self-Contrastive Forward-Forward Algorithm
by: Chen, Xing, et al.
Published: (2024)
by: Chen, Xing, et al.
Published: (2024)
Cumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant
by: Yousefiramandi, Amirhossein
Published: (2026)
by: Yousefiramandi, Amirhossein
Published: (2026)
Moonwalk: Inverse-Forward Differentiation
by: Krylov, Dmitrii, et al.
Published: (2024)
by: Krylov, Dmitrii, et al.
Published: (2024)
Selectivity and Shape in the Design of Forward-Forward Goodness Functions
by: Akkus, Talha Ruzgar, et al.
Published: (2026)
by: Akkus, Talha Ruzgar, et al.
Published: (2026)
FLOPS: Forward Learning with OPtimal Sampling
by: Ren, Tao, et al.
Published: (2024)
by: Ren, Tao, et al.
Published: (2024)
Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
by: As-Saquib, Nazmus Saadat, et al.
Published: (2025)
by: As-Saquib, Nazmus Saadat, et al.
Published: (2025)
Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networks
by: Terres-Escudero, Erik B., et al.
Published: (2024)
by: Terres-Escudero, Erik B., et al.
Published: (2024)
Optimizing Dense Feed-Forward Neural Networks
by: Balderas, Luis, et al.
Published: (2023)
by: Balderas, Luis, et al.
Published: (2023)
Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients
by: Flügel, Katharina, et al.
Published: (2024)
by: Flügel, Katharina, et al.
Published: (2024)
Learning Flexible Forward Trajectories for Masked Molecular Diffusion
by: Seo, Hyunjin, et al.
Published: (2025)
by: Seo, Hyunjin, et al.
Published: (2025)
Using Forwards-Backwards Models to Approximate MDP Homomorphisms
by: Mavor-Parker, Augustine N., et al.
Published: (2022)
by: Mavor-Parker, Augustine N., et al.
Published: (2022)
Forward Only Learning for Orthogonal Neural Networks of any Depth
by: Caillon, Paul, et al.
Published: (2025)
by: Caillon, Paul, et al.
Published: (2025)
Fast Forward: Accelerating LLM Prefill with Predictive FFN Sparsity
by: Gautam, Aayush, et al.
Published: (2026)
by: Gautam, Aayush, et al.
Published: (2026)
FwdLLM: Efficient FedLLM using Forward Gradient
by: Xu, Mengwei, et al.
Published: (2023)
by: Xu, Mengwei, et al.
Published: (2023)
On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning
by: Sun, Haoyuan, et al.
Published: (2025)
by: Sun, Haoyuan, et al.
Published: (2025)
Feed-Forward Optimization With Delayed Feedback for Neural Network Training
by: Flügel, Katharina, et al.
Published: (2023)
by: Flügel, Katharina, et al.
Published: (2023)
Thinking Forward and Backward: Effective Backward Planning with Large Language Models
by: Ren, Allen Z., et al.
Published: (2024)
by: Ren, Allen Z., et al.
Published: (2024)
Prefix Grouper: Efficient GRPO Training through Shared-Prefix Forward
by: Liu, Zikang, et al.
Published: (2025)
by: Liu, Zikang, et al.
Published: (2025)
Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
by: Yao, Yihang, et al.
Published: (2026)
by: Yao, Yihang, et al.
Published: (2026)
A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting
by: Caldas, Francisco, et al.
Published: (2026)
by: Caldas, Francisco, et al.
Published: (2026)
FLEX: Continuous Agent Evolution via Forward Learning from Experience
by: Cai, Zhicheng, et al.
Published: (2025)
by: Cai, Zhicheng, et al.
Published: (2025)
Forward versus Backward: Comparing Reasoning Objectives in Direct Preference Optimization
by: Nikzad, Murtaza, et al.
Published: (2026)
by: Nikzad, Murtaza, et al.
Published: (2026)
Spectral Alignment in Forward-Backward Representations via Temporal Abstraction
by: Azad, Seyed Mahdi B., et al.
Published: (2026)
by: Azad, Seyed Mahdi B., et al.
Published: (2026)
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
by: Wu, Tailin, et al.
Published: (2024)
by: Wu, Tailin, et al.
Published: (2024)
DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
by: Zhao, Gongpei, et al.
Published: (2024)
by: Zhao, Gongpei, et al.
Published: (2024)
Rethinking Forward Processes for Score-Based Nonlinear Data Assimilation in High Dimensions
by: Yoon, Eunbi, et al.
Published: (2026)
by: Yoon, Eunbi, et al.
Published: (2026)
Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks
by: Vexler, Julian, et al.
Published: (2025)
by: Vexler, Julian, et al.
Published: (2025)
Align Forward, Adapt Backward: Closing the Discretization Gap in Logic Gate Networks
by: Kim, Youngsung
Published: (2026)
by: Kim, Youngsung
Published: (2026)
Enhancing Fast Feed Forward Networks with Load Balancing and a Master Leaf Node
by: Charalampopoulos, Andreas, et al.
Published: (2024)
by: Charalampopoulos, Andreas, et al.
Published: (2024)
Revisiting Weak-to-Strong Generalization in Theory and Practice: Reverse KL vs. Forward KL
by: Yao, Wei, et al.
Published: (2025)
by: Yao, Wei, et al.
Published: (2025)
Looping Back to Move Forward: Recursive Transformers for Efficient and Flexible Large Multimodal Models
by: Xu, Ruihan, et al.
Published: (2026)
by: Xu, Ruihan, et al.
Published: (2026)
One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models
by: Cameron, Chris, et al.
Published: (2026)
by: Cameron, Chris, et al.
Published: (2026)
FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
by: Yu, Seunghun, et al.
Published: (2025)
by: Yu, Seunghun, et al.
Published: (2025)
Continual Learning: Applications and the Road Forward
by: Verwimp, Eli, et al.
Published: (2023)
by: Verwimp, Eli, et al.
Published: (2023)
Similar Items
-
Reshaping the Forward-Forward Algorithm with a Similarity-Based Objective
by: Gong, James, et al.
Published: (2025) -
Employing Layerwised Unsupervised Learning to Lessen Data and Loss Requirements in Forward-Forward Algorithms
by: Hwang, Taewook, et al.
Published: (2024) -
Hyperspherical Forward-Forward with Prototypical Representations
by: Sarode, Shalini, et al.
Published: (2026) -
Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
by: Ghader, Mohammadnavid, et al.
Published: (2025) -
Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm
by: Papachristodoulou, Andreas, et al.
Published: (2023)