Cover Image

Beyond Neural Networks: Symbolic Reasoning over Wavelet Logic Graph Signals

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kiruluta, Andrew, Lemos, Andreas, Burity, Priscilla
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

Operator-Based Machine Intelligence: A Hilbert Space Framework for Spectral Learning and Symbolic Reasoning
by: Kiruluta, Andrew, et al.
Published: (2025)

From Eigenmodes to Proofs: Integrating Graph Spectral Operators with Symbolic Interpretable Reasoning
by: Kiruluta, Andrew, et al.
Published: (2025)

Learnable Multi-Scale Wavelet Transformer: A Novel Alternative to Self-Attention
by: Kiruluta, Andrew, et al.
Published: (2025)

Wavelet Logic Machines: Learning and Reasoning in the Spectral Domain Without Neural Networks
by: Kiruluta, Andrew
Published: (2025)

Spectral Neuro-Symbolic Reasoning II: Semantic Node Merging, Entailment Filtering, and Knowledge Graph Alignment
by: Kiruluta, Andrew, et al.
Published: (2025)

Breaking Quadratic Barriers: A Non-Attention LLM for Ultra-Long Context Horizons
by: Kiruluta, Andrew, et al.
Published: (2025)

A Self-Supervised Reinforcement Learning Approach for Fine-Tuning Large Language Models Using Cross-Attention Signals
by: Kiruluta, Andrew, et al.
Published: (2025)

Beyond Self Attention: A Subquadratic Fourier Wavelet Transformer with Multi Modal Fusion
by: Kiruluta, Andrew, et al.
Published: (2021)

Graph Laplacian Wavelet Transformer via Learnable Spectral Decomposition
by: Kiruluta, Andrew, et al.
Published: (2025)

A Hybrid Wavelet-Fourier Method for Next-Generation Conditional Diffusion Models
by: Kiruluta, Andrew, et al.
Published: (2025)

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM
by: Kiruluta, Andrew, et al.
Published: (2025)

Data-Driven Variational Basis Learning Beyond Neural Networks: A Non-Neural Framework for Adaptive Basis Discovery
by: Kiruluta, Andrew
Published: (2026)

State Fourier Diffusion Language Model (SFDLM): A Scalable, Novel Iterative Approach to Language Modeling
by: Kiruluta, Andrew, et al.
Published: (2025)

Quantum Spectral Reasoning: A Non-Neural Architecture for Interpretable Machine Learning
by: Kiruluta, Andrew
Published: (2025)

From Pixels and Words to Waves: A Unified Framework for Spectral Dictionary vLLMs
by: Kiruluta, Andrew, et al.
Published: (2025)

Unsupervised Machine Learning Hybrid Approach Integrating Linear Programming in Loss Function: A Robust Optimization Technique
by: Kiruluta, Andrew, et al.
Published: (2024)

FourierNAT: A Fourier-Mixing-Based Non-Autoregressive Transformer for Parallel Sequence Generation
by: Kiruluta, Andrew, et al.
Published: (2025)

Entropic-Time Inference: Self-Organizing Large Language Model Decoding Beyond Attention
by: Kiruluta, Andrew
Published: (2026)

CS-VLM: Compressed Sensing Attention for Efficient Vision-Language Representation Learning
by: Kiruluta, Andrew, et al.
Published: (2025)

A Fully Spectral Neuro-Symbolic Reasoning Architecture with Graph Signal Processing as the Computational Backbone
by: Kiruluta, Andrew
Published: (2025)

Adaptive Two Sided Laplace Transforms: A Learnable, Interpretable, and Scalable Replacement for Self-Attention
by: Kiruluta, Andrew
Published: (2025)

Spectral Generative Flow Models: A Physics-Inspired Replacement for Vectorized Large Language Models
by: Kiruluta, Andrew
Published: (2026)

From Gradients to Riccati Geometry: Kalman World Models for Single-Pass Learning
by: Kiruluta, Andrew
Published: (2026)

Reducing Deep Network Complexity via Sparse Hierarchical Fourier Interaction Networks
by: Kiruluta, Andrew, et al.
Published: (2017)

Filtering Beats Fine Tuning: A Bayesian Kalman View of In Context Learning in LLMs
by: Kiruluta, Andrew
Published: (2026)

A Novel Architecture for Symbolic Reasoning with Decision Trees and LLM Agents
by: Kiruluta, Andrew
Published: (2025)

LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks
by: Geng, Chuqin, et al.
Published: (2025)

Logical Distillation of Graph Neural Networks
by: Pluska, Alexander, et al.
Published: (2024)

Neural Probabilistic Logic Learning for Knowledge Graph Reasoning
by: Sun, Fengsong, et al.
Published: (2024)

Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks
by: Grillo, Niccolò, et al.
Published: (2025)

A Logic for Reasoning About Aggregate-Combine Graph Neural Networks
by: Nunn, Pierre, et al.
Published: (2024)

WATS: Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling
by: Li, Xiaoyang, et al.
Published: (2025)

Quantum Circuit Reasoning Models: A Variational Framework for Differentiable Logical Inference
by: Kiruluta, Andrew
Published: (2025)

Reasoning Algorithmically in Graph Neural Networks
by: Numeroso, Danilo
Published: (2024)

SymAgent: A Neural-Symbolic Self-Learning Agent Framework for Complex Reasoning over Knowledge Graphs
by: Liu, Ben, et al.
Published: (2025)

Long-Range Graph Wavelet Networks
by: Guerranti, Filippo, et al.
Published: (2025)

Wavelet-based Variational Autoencoders for High-Resolution Image Generation
by: Kiruluta, Andrew
Published: (2025)

Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints
by: Geng, Chuqin, et al.
Published: (2026)

A Note on Graphon-Signal Analysis of Graph Neural Networks
by: Rauchwerger, Levi, et al.
Published: (2025)

Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
by: Fuchsgruber, Dominik, et al.
Published: (2024)