:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Luttermann, Malte, Möller, Ralf, Gehrke, Marcel
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2411.11730
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lifting Factor Graphs with Some Unknown Factors
by: Luttermann, Malte, et al.
Published: (2024)

Lifting Factor Graphs with Some Unknown Factors for New Individuals
by: Luttermann, Malte, et al.
Published: (2025)

On the Detection of Commutative Factors in Factor Graphs: Necessary and Sufficient Conditions
by: Luttermann, Malte, et al.
Published: (2026)

Approximate Lifted Model Construction
by: Luttermann, Malte, et al.
Published: (2025)

Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs
by: Luttermann, Malte, et al.
Published: (2024)

Efficient Detection of Commutative Factors in Factor Graphs
by: Luttermann, Malte, et al.
Published: (2024)

Lifted Causal Inference in Relational Domains
by: Luttermann, Malte, et al.
Published: (2024)

Towards Privacy-Preserving Relational Data Synthesis via Probabilistic Relational Models
by: Luttermann, Malte, et al.
Published: (2024)

Efficient Detection of Exchangeable Factors in Factor Graphs
by: Luttermann, Malte, et al.
Published: (2024)

Compression versus Accuracy: A Hierarchy of Lifted Models
by: Speller, Jan, et al.
Published: (2025)

Denoising the Future: Top-p Distributions for Moving Through Time
by: Marwitz, Florian Andreas, et al.
Published: (2025)

Lifted Forward Planning in Relational Factored Markov Decision Processes with Concurrent Actions
by: Marwitz, Florian Andreas, et al.
Published: (2025)

On the Completeness and Complexity of the Lifted Dynamic Junction Tree Algorithm
by: Gehrke, Marcel
Published: (2021)

Transformer Normalisation Layers and the Independence of Semantic Subspaces
by: Menary, Stephen, et al.
Published: (2024)

Exploiting Symmetry in Dynamics for Model-Based Reinforcement Learning with Asymmetric Rewards
by: Sonmez, Yasin, et al.
Published: (2024)

Deep Learning without Weight Symmetry
by: Ji-An, Li, et al.
Published: (2024)

CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
by: Park, Jongwon, et al.
Published: (2025)

ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning
by: Yu, Xin, et al.
Published: (2023)

Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
by: Li, Mingchen, et al.
Published: (2025)

Enhancement of Subjective Content Descriptions by using Human Feedback
by: Bender, Magnus, et al.
Published: (2024)

Symmetry-Aware Graph Metanetwork Autoencoders: Model Merging through Parameter Canonicalization
by: Boufalis, Odysseas, et al.
Published: (2025)

Graph Transformers without Positional Encodings
by: Garg, Ayush
Published: (2024)

Tailored Architectures for Time Series Forecasting: Evaluating Deep Learning Models on Gaussian Process-Generated Data
by: Hankemeier, Victoria, et al.
Published: (2025)

Mechanisms for Data Sharing in Collaborative Causal Inference (Extended Version)
by: Filter, Björn, et al.
Published: (2024)

Security and Detectability Analysis of Unicode Text Watermarking Methods Against Large Language Models
by: Hellmeier, Malte
Published: (2025)

HUGO -- Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach
by: Lehna, Malte, et al.
Published: (2024)

Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
by: Mirzaei, Erfan, et al.
Published: (2026)

CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data Augmentations
by: Zhang, Tianyu, et al.
Published: (2021)

Class-Imbalanced Graph Learning without Class Rebalancing
by: Liu, Zhining, et al.
Published: (2023)

Towards Effective and Efficient Graph Alignment without Supervision
by: Chen, Songyang, et al.
Published: (2026)

From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding
by: Cai, Borui, et al.
Published: (2023)

Optimizing Job Shop Scheduling in the Furniture Industry: A Reinforcement Learning Approach Considering Machine Setup, Batch Variability, and Intralogistics
by: Schneevogt, Malte, et al.
Published: (2024)

Learning Causal Graphs at Scale: A Foundation Model Approach
by: Yin, Naiyu, et al.
Published: (2025)

Differentiable Learning of Lifted Action Schemas for Classical Planning
by: Reiter, Jonas, et al.
Published: (2026)

SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs
by: Chen, Hanzhu, et al.
Published: (2024)

CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in Variational AutoEncoder
by: Jung, Hee-Jun, et al.
Published: (2024)

Learning Fair Models without Sensitive Attributes: A Generative Approach
by: Zhu, Huaisheng, et al.
Published: (2022)

Deploying Models to Non-participating Clients in Federated Learning without Fine-tuning: A Hypernetwork-based Approach
by: Zhou, Yuhao, et al.
Published: (2025)

Similarity-Based Self-Construct Graph Model for Predicting Patient Criticalness Using Graph Neural Networks and EHR Data
by: Sahu, Mukesh Kumar, et al.
Published: (2025)

Exploiting Block Coordinate Descent for Cost-Effective LLM Model Training
by: Liu, Zeyu, et al.
Published: (2025)