Cover Image

Topological Deep Learning: A Review of an Emerging Paradigm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zia, Ali, Khamis, Abdelwahed, Nichols, James, Hayder, Zeeshan, Rolland, Vivien, Petersson, Lars
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
by: Khamis, Abdelwahed, et al.
Published: (2023)

NeuralPrefix: A Zero-shot Sensory Data Imputation Plugin
by: Khamis, Abdelwahed, et al.
Published: (2025)

A Review on Coarse to Fine-Grained Animal Action Recognition
by: Zia, Ali, et al.
Published: (2025)

Test-Time Adaptation for Anomaly Segmentation via Topology-Aware Optimal Transport Chaining
by: Zia, Ali, et al.
Published: (2026)

A Complete Survey on Contemporary Methods, Emerging Paradigms and Hybrid Approaches for Few-Shot Learning
by: Tsoumplekas, Georgios, et al.
Published: (2024)

A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning
by: Fakour, Fahimeh, et al.
Published: (2024)

Emerging Paradigms for Securing Federated Learning Systems
by: Abouelmagd, Amr Akmal, et al.
Published: (2025)

GATech at AbjadMed: Bidirectional Encoders vs. Causal Decoders: Insights from 82-Class Arabic Medical Classification
by: Khamis, Ahmed Khaled
Published: (2026)

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
by: Lu, Haoran, et al.
Published: (2025)

Learning Associative Memories with Gradient Descent
by: Cabannes, Vivien, et al.
Published: (2024)

A Review of Deep Learning Approaches for Non-Invasive Cognitive Impairment Detection
by: Alsuhaibani, Muath, et al.
Published: (2024)

WS-Net: Weak-Signal Representation Learning and Gated Abundance Reconstruction for Hyperspectral Unmixing via State-Space and Weak Signal Attention Fusion
by: Long, Zekun, et al.
Published: (2026)

Periodic Topological Deep Learning for Polymer Design and Discovery
by: Yadav, Yasharth, et al.
Published: (2026)

Advancing Deep Learning through Probability Engineering: A Pragmatic Paradigm for Modern AI
by: Zhang, Jianyi
Published: (2025)

Emerging Synergies in Causality and Deep Generative Models: A Survey
by: Zhou, Guanglin, et al.
Published: (2023)

Physics-Assisted and Topology-Informed Deep Learning for Weather Prediction
by: Zheng, Jiaqi, et al.
Published: (2025)

Learning with Hidden Factorial Structure
by: Arnal, Charles, et al.
Published: (2024)

Controllable Data Generation by Deep Learning: A Review
by: Wang, Shiyu, et al.
Published: (2022)

Touring sampling with pushforward maps
by: Cabannes, Vivien, et al.
Published: (2023)

The Galerkin method beats Graph-Based Approaches for Spectral Algorithms
by: Cabannes, Vivien, et al.
Published: (2023)

Deep Learning Based Situation Awareness for Multiple Missiles Evasion
by: Scukins, Edvards, et al.
Published: (2024)

Provable Benefits of In-Tool Learning for Large Language Models
by: Houliston, Sam, et al.
Published: (2025)

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
by: Bernárdez, Guillermo, et al.
Published: (2024)

Topological Deep Learning with State-Space Models: A Mamba Approach for Simplicial Complexes
by: Montagna, Marco, et al.
Published: (2024)

Topology-Aware and Highly Generalizable Deep Reinforcement Learning for Efficient Retrieval in Multi-Deep Storage Systems
by: Li, Funing, et al.
Published: (2025)

FloydNet: A Learning Paradigm for Global Relational Reasoning
by: Yu, Jingcheng, et al.
Published: (2026)

Nested Learning: The Illusion of Deep Learning Architectures
by: Behrouz, Ali, et al.
Published: (2025)

Critical Learning Periods Emerge Even in Deep Linear Networks
by: Kleinman, Michael, et al.
Published: (2023)

ArrhythmiaVision: Resource-Conscious Deep Learning Models with Visual Explanations for ECG Arrhythmia Classification
by: Baig, Zuraiz, et al.
Published: (2025)

Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
by: Zhou, Yicheng, et al.
Published: (2024)

Learning in Context, Guided by Choice: A Reward-Free Paradigm for Reinforcement Learning with Transformers
by: Dong, Juncheng, et al.
Published: (2026)

FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated Clients
by: Shen, Leming, et al.
Published: (2025)

In-Context Learning Strategies Emerge Rationally
by: Wurgaft, Daniel, et al.
Published: (2025)

Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception
by: Mueller, Phillip, et al.
Published: (2024)

A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
by: Guarrasi, Valerio, et al.
Published: (2024)

A Brief Review for Compression and Transfer Learning Techniques in DeepFake Detection
by: Karathanasis, Andreas, et al.
Published: (2025)

Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms
by: Peng, Yuanzhe, et al.
Published: (2025)

Artificial Intelligence and Deep Learning Algorithms for Epigenetic Sequence Analysis: A Review for Epigeneticists and AI Experts
by: Tahir, Muhammad, et al.
Published: (2025)

Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry
by: Mayr, Michael, et al.
Published: (2024)

Deep Heuristic Learning for Real-Time Urban Pathfinding
by: El-Ela, Mohamed Hussein Abo, et al.
Published: (2024)