:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Baeuerle, Simon, Gebhardt, Marius, Barth, Jonas, Steimer, Andreas, Mikut, Ralf
Format:	Preprint
Published:	2022
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2208.04045
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Coverage Path Planning for Thermal Interface Materials
by: Baeuerle, Simon, et al.
Published: (2024)

Rapid AI-based generation of coverage paths for dispensing applications
by: Baeuerle, Simon, et al.
Published: (2025)

Are Foundation Models Ready for Industrial Defect Recognition? A Reality Check on Real-World Data
by: Baeuerle, Simon, et al.
Published: (2025)

Iterative Cluster Harvesting for Wafer Map Defect Patterns
by: Pleli, Alina, et al.
Published: (2024)

EmbedTrack -- Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths
by: Löffler, Katharina, et al.
Published: (2022)

Knowledge Distillation for Efficient Transformer-Based Reinforcement Learning in Hardware-Constrained Energy Management Systems
by: Henrich, Pascal, et al.
Published: (2026)

LeDiFlow: Learned Distribution-guided Flow Matching to Accelerate Image Generation
by: Zwick, Pascal, et al.
Published: (2025)

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models
by: Hertel, Matthias, et al.
Published: (2026)

Explainable time-series forecasting with sampling-free SHAP for Transformers
by: Hertel, Matthias, et al.
Published: (2025)

Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning
by: Fehring, Lukas, et al.
Published: (2025)

Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling
by: Schynol, Lukas, et al.
Published: (2024)

Self-Supervised Learning Strategies for a Platform to Test the Toxicity of New Chemicals and Materials
by: Lautenschlager, Thomas, et al.
Published: (2025)

Structural Connectome Harmonization Using Deep Learning: The Strength of Graph Neural Networks
by: Patel, Jagruti, et al.
Published: (2025)

Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks
by: Hennig, Leona, et al.
Published: (2024)

Learning Guarantee of Reward Modeling Using Deep Neural Networks
by: Luo, Yuanhang, et al.
Published: (2025)

Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)

State Derivative Normalization for Continuous-Time Deep Neural Networks
by: Weigand, Jonas, et al.
Published: (2024)

Modeling Behavioral Patterns in News Recommendations Using Fuzzy Neural Networks
by: Innerebner, Kevin, et al.
Published: (2026)

DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights
by: Gupta, Saumya, et al.
Published: (2026)

Introducing a Deep Neural Network-based Model Predictive Control Framework for Rapid Controller Implementation
by: Gordon, David C., et al.
Published: (2023)

Generating peak-aware pseudo-measurements for low-voltage feeders using metadata of distribution system operators
by: Treutlein, Manuel, et al.
Published: (2024)

AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability
by: Meisenbacher, Stefan, et al.
Published: (2024)

Invariant Control Strategies for Active Flow Control using Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)

Explainable Threat Attribution for IoT Networks Using Conditional SHAP and Flow Behavior Modelling
by: Ozechi, Samuel, et al.
Published: (2026)

Recurrent Deep Differentiable Logic Gate Networks
by: Bührer, Simon, et al.
Published: (2025)

Towards a Systematic Risk Assessment of Deep Neural Network Limitations in Autonomous Driving Perception
by: Pavlitska, Svetlana, et al.
Published: (2026)

Runtime Safety Monitoring of Deep Neural Networks for Perception: A Survey
by: Schotschneider, Albert, et al.
Published: (2025)

Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks
by: Mattey, Revanth, et al.
Published: (2024)

EBGAN-MDN: An Energy-Based Adversarial Framework for Multi-Modal Behavior Cloning
by: Li, Yixiao, et al.
Published: (2025)

Template-Fitting Meets Deep Learning: Redshift Estimation Using Physics-Guided Neural Networks
by: Ferrao, Jonas Chris, et al.
Published: (2025)

Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models
by: Bogdoll, Daniel, et al.
Published: (2021)

Efficient Training of Probabilistic Neural Networks for Survival Analysis
by: Lillelund, Christian Marius, et al.
Published: (2024)

Comgra: A Tool for Analyzing and Debugging Neural Networks
by: Dietz, Florian, et al.
Published: (2024)

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models
by: Deng, Difan, et al.
Published: (2026)

Geometric Flow Models over Neural Network Weights
by: Erdogan, Ege
Published: (2025)

The Connection between Kriging and Large Neural Networks
by: Marinescu, Marius
Published: (2026)

Evolvable Psychology Informed Neural Network for Memory Behavior Modeling
by: Shen, Xiaoxuan, et al.
Published: (2024)

Deep Causal Behavioral Policy Learning: Applications to Healthcare
by: Knecht, Jonas, et al.
Published: (2025)

Decision-Focused Fine-Tuning of Time Series Foundation Models for Dispatchable Feeder Optimization
by: Beichter, Maximilian, et al.
Published: (2025)

Reduced Optimal Power Flow Using Graph Neural Network
by: Pham, Thuan, et al.
Published: (2022)