Hugging Face Trending Papers
Nonlinear Direct Feedback Alignment for Scalable Backpropagation-Free Training
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arXiv Machine Learning
Jun 10
Overcoming Rank Collapse in Feedback Alignment
arXiv:2606. 11123v1 Announce Type: new Abstract: Backpropagation (BP) is widely viewed as biologically implausible, in part because it requires feedback weights to be the transpose of forward weights for error propagation.
arXiv Machine Learning
Jun 11
Understanding Sample Efficiency in Predictive Coding
arXiv:2605. 11911v2 Announce Type: replace Abstract: Predictive Coding (PC) is an influential account of cortical learning.
arXiv Machine Learning
Oct 9
LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression
LAIR-Net is a Leaky Alignment-Impulse Residual Network designed for tabular regression that incorporates a shallow learned anchor into each hidden state via a leaky residual transition. The authors provide a depth‑uniform bound on input‑perturbation sensitivity and show through controlled simulations that performance gains over randomized baselines stem from the anchor rather than recursion or added capacity. On 23 benchmark datasets, LAIR‑Net achieves the best average rank among eight randomized networks and twelve conventional models, with its success linked to the presence of nonlinear target structure and manageable noise levels.
arXiv Machine Learning
Oct 22
Progressive Permutation Alignment with Temperature-Controlled Spectral Sharpening
The paper introduces a progressive permutation alignment technique for implicit neural representations, using layer-wise correlation estimation, Hungarian matching, and temperature-controlled spectral annealing to gradually sharpen the alignment toward a permutation matrix. This deterministic, lightweight method avoids costly gradient optimization and is followed by a final refinement stage that optimizes layer-by-layer weight matching. Experiments on MLPs, CNNs, and NeRFs demonstrate reliable neuron correspondence recovery and reduced loss barriers during weight interpolation.
arXiv AI
Jun 10
Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment
arXiv:2606. 09928v1 Announce Type: cross Abstract: The Forward-Forward (FF) algorithm offers a biologically inspired alternative to backpropagation by replacing gradient-based credit assignment with local, forward-only objectives.
Hugging Face Trending Papers
Oct 21
Progressive Permutation Alignment with Temperature-Controlled Spectral Sharpening
In implicit neural representations (INRs), 3D signals are encoded directly in network weights, making stable weight-space operations essential. However, permutation symmetry causes independently train...