Image de couverture de livre

A Relational Inductive Bias for Dimensional Abstraction in Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Campbell, Declan, Cohen, Jonathan D.
Format:	Preprint
Publié:	2024
Sujets:	Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

The Relational Bottleneck as an Inductive Bias for Efficient Abstraction
par: Webb, Taylor W., et autres
Publié: (2023)

Understanding Task Representations in Neural Networks via Bayesian Ablation
par: Nam, Andrew, et autres
Publié: (2025)

Human-Like Geometric Abstraction in Large Pre-trained Neural Networks
par: Campbell, Declan, et autres
Publié: (2024)

Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks
par: Bencomo, Gianluca, et autres
Publié: (2025)

Compositional Sparsity as an Inductive Bias for Neural Architecture Design
par: Lin, Hongyu, et autres
Publié: (2026)

Group Relative Knowledge Distillation: Learning from Teacher's Relational Inductive Bias
par: Li, Chao, et autres
Publié: (2025)

Neural Causal Abstractions
par: Xia, Kevin, et autres
Publié: (2024)

Disentangling Granularity: An Implicit Inductive Bias in Factorized VAEs
par: Chen, Zihao, et autres
Publié: (2025)

Soft Geometric Inductive Bias for Object Centric Dynamics
par: Linander, Hampus, et autres
Publié: (2025)

Combining Causal Models for More Accurate Abstractions of Neural Networks
par: Pîslar, Theodora-Mara, et autres
Publié: (2025)

Program Synthesis using Inductive Logic Programming for the Abstraction and Reasoning Corpus
par: Rocha, Filipe Marinho, et autres
Publié: (2024)

Clustering Inductive Biases with Unrolled Networks
par: Huml, Jonathan, et autres
Publié: (2023)

Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges
par: Kosman, Eitan, et autres
Publié: (2026)

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance
par: Li, Zhuo, et autres
Publié: (2025)

Self-Abstraction Learning for Effective and Stable Training of Deep Neural Networks
par: Cho, Wonyong, et autres
Publié: (2026)

Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoning
par: Dong, Hao, et autres
Publié: (2023)

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
par: Liu, Yang, et autres
Publié: (2023)

MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction
par: Martell, Marc Boubnovski, et autres
Publié: (2026)

Explaining Neural Networks in Preference Learning: a Post-hoc Inductive Logic Programming Approach
par: Fossemò, Daniele, et autres
Publié: (2026)

On the Inductive Bias of Stacking Towards Improving Reasoning
par: Saunshi, Nikunj, et autres
Publié: (2024)

Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control
par: Jiralerspong, Thomas, et autres
Publié: (2025)

Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers
par: Sankaran, Shyam, et autres
Publié: (2026)

Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction
par: Liu, Tianyu, et autres
Publié: (2024)

Learning Consistent Causal Abstraction Networks
par: D'Acunto, Gabriele, et autres
Publié: (2026)

Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction
par: Adeseye, Aisvarya, et autres
Publié: (2026)

What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models
par: Vafa, Keyon, et autres
Publié: (2025)

Training the Untrainable: Introducing Inductive Bias via Representational Alignment
par: Subramaniam, Vighnesh, et autres
Publié: (2024)

An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention
par: Shin, Yehjin, et autres
Publié: (2023)

Networks of Causal Abstractions: A Sheaf-theoretic Framework
par: D'Acunto, Gabriele, et autres
Publié: (2025)

Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning
par: Cohen, Nadav, et autres
Publié: (2024)

What Structural Inductive Bias Helps Transformers Reason Over Knowledge Graphs? A Study with Tabula RASA
par: Petersen, Jonas, et autres
Publié: (2026)

Investigating Relational State Abstraction in Collaborative MARL
par: Utke, Sharlin, et autres
Publié: (2024)

Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification
par: Asiaee, Amir
Publié: (2026)

PLOT: Progressive Localization via Optimal Transport in Neural Causal Abstraction
par: Chang, Jonathn, et autres
Publié: (2026)

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
par: Hu, Yuanzhe, et autres
Publié: (2025)

Bound by semanticity: universal laws governing the generalization-identification tradeoff
par: Nurisso, Marco, et autres
Publié: (2025)

SBS: Enhancing Parameter-Efficiency of Neural Representations for Neural Networks via Spectral Bias Suppression
par: Xie, Qihu, et autres
Publié: (2025)

Inductive Moment Matching
par: Zhou, Linqi, et autres
Publié: (2025)

ARC-GEN: A Mimetic Procedural Benchmark Generator for the Abstraction and Reasoning Corpus
par: Moffitt, Michael D.
Publié: (2025)

Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
par: Fang, Ronglong, et autres
Publié: (2024)