Cover Image

Single-Core Superscalar Optimization of Clifford Neural Layers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, X. Angelo, Ciranni, Ruben, Spadaccini, Giovanni, Zurita, Carla J. López
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fast Clifford Neural Layers
by: Xia, Tianxiang, et al.
Published: (2025)

Discovery and inference beyond linearity by integrating Bayesian regression, tree ensembles and Shapley values
by: Spadaccini, Giorgio, et al.
Published: (2025)

Mean-Field Limits for Two-Layer Neural Networks Trained with Consensus-Based Optimization
by: De Deyn, William, et al.
Published: (2025)

COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations
by: Ciranni, Ruben, et al.
Published: (2024)

Clifford-Steerable Convolutional Neural Networks
by: Zhdanov, Maksim, et al.
Published: (2024)

Metric Learning for Clifford Group Equivariant Neural Networks
by: Ali, Riccardo, et al.
Published: (2024)

Neural Co-Optimization of Structural Topology, Manufacturable Layers, and Path Orientations for Fiber-Reinforced Composites
by: Liu, Tao, et al.
Published: (2025)

NetworkFF: Unified Layer Optimization in Forward-Only Neural Networks
by: Beigzad, Salar
Published: (2025)

A Clifford Algebraic Approach to E(n)-Equivariant High-order Graph Neural Networks
by: Tran, Viet-Hoang, et al.
Published: (2024)

SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators
by: Elhadidy, Mahmoud, et al.
Published: (2026)

ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
by: Parkinson, Suzanna, et al.
Published: (2023)

Differentiable Convex Optimization Layers in Neural Architectures: Foundations and Perspectives
by: Katyal, Calder
Published: (2024)

FedStale: leveraging stale client updates in federated learning
by: Rodio, Angelo, et al.
Published: (2024)

UniHetCO: A Unified Heterogeneous Representation for Multi-Problem Learning in Unsupervised Neural Combinatorial Optimization
by: Nguyen, Kien X., et al.
Published: (2026)

Looking at Model Debiasing through the Lens of Anomaly Detection
by: Pastore, Vito Paolo, et al.
Published: (2024)

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization
by: Wu, Ka Wai
Published: (2024)

Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks
by: Liu, Cong, et al.
Published: (2024)

Half-Layered Neural Networks
by: Alpaydin, Ethem
Published: (2025)

C3PO: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing
by: Li, Zhongyang, et al.
Published: (2025)

Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements
by: Grewal, Sabee, et al.
Published: (2023)

Targeted Unlearning with Single Layer Unlearning Gradient
by: Cai, Zikui, et al.
Published: (2024)

Clifford Kolmogorov-Arnold Networks
by: Wolff, Matthias, et al.
Published: (2026)

Rethinking Layer-wise Model Merging through Chain of Merges
by: Buzzega, Pietro, et al.
Published: (2025)

Simultaneous Weight and Architecture Optimization for Neural Networks
by: Huang, Zitong, et al.
Published: (2024)

Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
by: Sun, Guoze, et al.
Published: (2026)

DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
by: Pal, Shraman, et al.
Published: (2026)

DeepBaR: Fault Backdoor Attack on Deep Neural Network Layers
by: Martínez-Mejía, C. A., et al.
Published: (2024)

How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis
by: Higuchi, Rei, et al.
Published: (2026)

Layer-to-Layer Knowledge Mixing in Graph Neural Network for Chemical Property Prediction
by: See, Teng Jiek, et al.
Published: (2025)

Say My Name: a Model's Bias Discovery Framework
by: Ciranni, Massimiliano, et al.
Published: (2024)

DFReg: A Physics-Inspired Framework for Global Weight Distribution Regularization in Neural Networks
by: Ruggieri, Giovanni
Published: (2025)

Closed-Form Last Layer Optimization
by: Galashov, Alexandre, et al.
Published: (2025)

Comparing Methods for Bias Mitigation in Graph Neural Networks
by: Hoffmann, Barbara, et al.
Published: (2025)

Physics-Constrained Adaptive Neural Networks Enable Real-Time Semiconductor Manufacturing Optimization with Minimal Training Data
by: Guerrero, Rubén Darío
Published: (2025)

Mathematical Modeling and Convergence Analysis of Deep Neural Networks with Dense Layer Connectivities in Deep Learning
by: Huang, Jinshu, et al.
Published: (2025)

Personalized Layer Selection for Graph Neural Networks
by: Sharma, Kartik, et al.
Published: (2025)

A Lightweight and Gradient-Stable Neural Layer
by: Yu, Yueyao, et al.
Published: (2021)

Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
by: Fang, Jiaxun, et al.
Published: (2025)

Bayesian full waveform inversion with sequential surrogate model refinement
by: Meles, Giovanni Angelo, et al.
Published: (2025)

Embedding Knowledge Graphs in Degenerate Clifford Algebras
by: Teyou, Louis Mozart Kamdem, et al.
Published: (2024)