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🔍 andreas eberle 📂 AI & Data Science
Showing 76790 results for "andreas eberle" in AI & Data Science
AI & Data Science Preprint PDF DOI

An adaptive wavelet-based PINN for problems with localized high-magnitude source

Himanshu Pandey, Ratikanta Behera · 2026

In recent years, physics-informed neural networks (PINNs) have gained significant attention for solving differential equations, although they suffer from two fundamental limitations, namely, spectral …

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AI & Data Science Preprint PDF DOI

Action Motifs: Self-Supervised Hierarchical Representation of Human Body Movements

Genki Kinoshita, Shu Nakamura, Ryo Kawahara, Shohei Nobuhara, Yasutomo Kawanishi, Ko Nishino · 2026

Effective human behavior modeling requires a representation of the human body movement that capitalizes on its compositionality. We propose a hierarchical representation consisting of Action Atoms tha…

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Continuous-tone Simple Points: An $\ell_0$-Norm of Cyclic Gradient for Topology-Preserving Data-Driven Image Segmentation

Wenxiao Li, Faqiang Wang, Yuping Duan, Li Cui, Liqiang Zhang, Jun Liu · 2026

Topological features play an essential role in ensuring geometric plausibility and structural consistency in image analysis tasks such as segmentation and skeletonization. However, integrating topolog…

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AI & Data Science Preprint PDF DOI

Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

Yujun Wu, Dongxu Zhang, Xinchen Li, Jinhang Xu, Yiling Duan, Yumou Liu, Jiabao Pan, Xuanhe Zhou, Jingxuan Wei, Siyuan Li, Jintao Chen, Conghui He, Cheng Tan · 2026

Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In particular, it does not…

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AI & Data Science Preprint PDF DOI

Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression

Junqi Gao, Dazhi Zhang, Zhichang Guo, Biqing Qi, Yi Ran, Wangmeng Zuo · 2026

Model merging has attracted attention as an effective path toward multi-task adaptation by integrating knowledge from multiple task-specific models. Among existing approaches, dynamic merging mitigate…

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AI & Data Science Preprint PDF DOI

Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments

Akhil Gupta, Erhan Guven · 2026

Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracking of adversarial unmanned aerial vehicles (UAVs…

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AI & Data Science Preprint PDF DOI

FiLMMeD: Feature-wise Linear Modulation for Cross-Problem Multi-Depot Vehicle Routing

Arthur Correa, Paulo Nascimento, Samuel Moniz · 2026

Solving practical multi-depot vehicle routing problems (MDVRP) is a challenging optimization task central to modern logistics, increasingly driven by e-commerce. To address the MDVRP's computational c…

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AI & Data Science Preprint PDF DOI

UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation

Shuokun Cheng, Jinghao Shi, Kun Sun · 2026

Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit ill-defined boundaries, leading to unstable predi…

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AI & Data Science Preprint PDF DOI

Agent-Agnostic Evaluation of SQL Accuracy in Production Text-to-SQL Systems

Taslim Jamal Arif, Kuldeep Singh · 2026

Text-to-SQL (T2SQL) evaluation in production environments poses fundamental challenges that existing benchmarks do not address. Current evaluation methodologies whether rule-based SQL matching or sche…

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Ease of dependency distance minimization in star-like structures

Emilia Garcia-Casademont, Ramon Ferrer-i-Cancho · 2026

The syntactic structure of a sentence can be represented as a tree where edges indicate syntactic dependencies between words. When that structure is a star, it has been demonstrated that the head shou…

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Shuffling-Aware Optimization for Private Vector Mean Estimation

Shun Takagi, Seng Pei Liew · 2026

We study $d$-dimensional unbiased mean estimation in the single-message shuffle model, where each user sends a single privatized message and the analyzer only observes the shuffled multiset of reports…

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MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness

Jeanne Monnier, Thomas George, Frederic Guyard, Christele Tarnec, Marios Kountouris · 2026

Fairness in machine learning remains challenging due to its ethical complexity, the absence of a universal definition, and the need for context-specific bias metrics. Existing methods still struggle w…

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AI & Data Science Preprint PDF DOI

Response to: "A note on conditional densities, Bayes' rule, and recent criticisms of Bayesian inference" by Yan et al., 2026

Klaus Mosegaard, Andrew Curtis · 2026

In a recent preprint (Mosegaard and Curtis, 2024, arXiv:2411.13570v2) we analyzed the consequences of ignoring the well-known inconsistency of classical conditional probability densities. We explained…

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AI & Data Science Preprint PDF DOI

FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning

Zhiqiang Kou, Junxiang Wu, Wenke Huang, Wenwen He, Ming-Kun Xie, Changwei Wang, Yuheng Jia, Di Jiang, Yang Liu, Xin Geng, Qiang Yang · 2026

Federated Multi-Label Learning is a distributed paradigm where multiple clients possess heterogeneous multi-label data and perform collaborative learning under privacy constraints without sharing raw …

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AI & Data Science Preprint PDF DOI

Are DeepFakes Realistic Enough? Exploring Semantic Mismatch as a Novel Challenge

Sharayu Nilesh Deshmukh, Kailash A. Hambarde, Joana C. Costa, Hugo Proenca, Tiago Roxo · 2026

Current DeepFake detection scenarios are mostly binary, yet data manipulation can vary across audio, video, or both, whose variability is not captured in binary settings. Four-class audio-visual formu…

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Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning

Shijin Gong, Kai Ye, Jin Zhu, Xinyu Zhang, Hongyi Zhou, Chengchun Shi · 2026

Recent advances in large language models (LLMs) have increasingly relied on reinforcement learning (RL) to improve their reasoning capabilities. Three approaches have been widely adopted: (i) Proximal…

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AI & Data Science Preprint PDF DOI

Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning

Jingcheng Deng, Zihao Wei, Liang Pang, Junhong Wu, Shicheng Xu, Zenghao Duan, Huawei Shen · 2026

Latent reasoning offers a more efficient alternative to explicit reasoning by compressing intermediate reasoning into continuous representations and substantially shortening reasoning chains. However,…

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AI & Data Science Preprint PDF DOI

Dynamic Scaled Gradient Descent for Stable Fine-Tuning for Classifications

Nghia Bui, Lijing Wang · 2026

Fine-tuning pretrained models has become a standard approach to adapting pretrained knowledge to improve the accuracy on new sparse, imbalance datasets. However, issues arise when optimization falls i…

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AI & Data Science Preprint PDF DOI

TransVLM: A Vision-Language Framework and Benchmark for Detecting Any Shot Transitions

Ce Chen, Yi Ren, Yuanming Li, Viktor Goriachko, Zhenhui Ye, Zujin Guo, Zhibin Hong, Mingming Gong · 2026

Traditional Shot Boundary Detection (SBD) inherently struggles with complex transitions by formulating the task around isolated cut points, frequently yielding corrupted video shots. We address this f…

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FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting

Fengxian Ji, Jingpu Yang, Zirui Song, Yuanxi Wang, Zhexuan Cui, Yuke Li, Qian Jiang, Xiuying Chen · 2026

Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage, imprecise target-st…

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