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Marius Kloft

Identifiers

  • name variant Marius Kloft 0.60 · backfill

Papers (67)

  1. Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods stat.ML · 2026 · author #4
  2. Population Risk Bounds for Kolmogorov-Arnold Networks Trained by DP-SGD with Correlated Noise cs.LG · 2026 · author #7
  3. Skipping the Zeros in Diffusion Models for Sparse Data Generation cs.LG · 2026 · author #8
  4. Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks cs.LG · 2026 · author #4
  5. PIANO: Physics Informed Autoregressive Network cs.LG · 2025 · author #4
  6. Continual Neural Topic Model cs.LG · 2025 · author #3
  7. Multi-level Supervised Contrastive Learning cs.LG · 2025 · author #6
  8. Challenging Assumptions in Learning Generic Text Style Embeddings cs.LG · 2025 · author #2
  9. Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings cs.LG · 2024 · author #7
  10. SetPINNs: Set-based Physics-informed Neural Networks cs.LG · 2024 · author #7
  11. Comgra: A Tool for Analyzing and Debugging Neural Networks cs.LG · 2024 · author #4
  12. Anomaly Detection of Tabular Data Using LLMs cs.LG · 2024 · author #4
  13. AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics cs.AI · 2024 · author #7
  14. Interpretable Tensor Fusion cs.LG · 2024 · author #7
  15. On the Challenges and Opportunities in Generative AI cs.LG · 2024 · author #11
  16. Labeling Neural Representations with Inverse Recognition cs.LG · 2023 · author #4
  17. Evaluating Dynamic Topic Models cs.CL · 2023 · author #4
  18. Text Style Transfer Evaluation Using Large Language Models cs.CL · 2023 · author #3
  19. A Call for Standardization and Validation of Text Style Transfer Evaluation cs.LG · 2023 · author #3
  20. Deep Anomaly Detection on Tennessee Eastman Process Data cs.LG · 2023 · author #18
  21. Zero-Shot Anomaly Detection via Batch Normalization cs.LG · 2023 · author #3
  22. Deep Anomaly Detection under Labeling Budget Constraints cs.LG · 2023 · author #3
  23. Ordinal Regression for Difficulty Estimation of StepMania Levels cs.LG · 2023 · author #4
  24. Generalization Bounds for Inductive Matrix Completion in Low-noise Settings cs.LG · 2022 · author #5
  25. Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings cs.LG · 2022 · author #3
  26. Training Normalizing Flows from Dependent Data cs.LG · 2022 · author #3
  27. Making Thermodynamic Models of Mixtures Predictive by Machine Learning: Matrix Completion of Pair Interactions physics.chem-ph · 2022 · author #5
  28. Raising the Bar in Graph-level Anomaly Detection cs.LG · 2022 · author #2
  29. Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images cs.CV · 2022 · author #6
  30. Latent Outlier Exposure for Anomaly Detection with Contaminated Data cs.LG · 2022 · author #3
  31. Detecting Anomalies within Time Series using Local Neural Transformations cs.LG · 2022 · author #3
  32. A systematic approach to random data augmentation on graph neural networks cs.LG · 2021 · author #3
  33. Explainability Requires Interactivity cs.LG · 2021 · author #3
  34. Fine-grained Generalization Analysis of Structured Output Prediction cs.LG · 2021 · author #4
  35. Fine-grained Generalization Analysis of Vector-valued Learning cs.LG · 2021 · author #4
  36. Neural Transformation Learning for Deep Anomaly Detection Beyond Images cs.LG · 2021 · author #3
  37. A Unifying Review of Deep and Shallow Anomaly Detection cs.LG · 2020 · author #6
  38. Input Hessian Regularization of Neural Networks cs.LG · 2020 · author #3
  39. Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events cs.CV · 2020 · author #7
  40. Explainable Deep One-Class Classification cs.CV · 2020 · author #5
  41. How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks cs.LG · 2020 · author #5
  42. Rethinking Assumptions in Deep Anomaly Detection cs.LG · 2020 · author #5
  43. Orthogonal Inductive Matrix Completion cs.LG · 2020 · author #3
  44. Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion physics.chem-ph · 2020 · author #8
  45. Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification cs.LG · 2020 · author #3
  46. Two-sample Testing Using Deep Learning stat.ML · 2019 · author #3
  47. Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator cs.LG · 2019 · author #4
  48. Deep Semi-Supervised Anomaly Detection cs.LG · 2019 · author #7
  49. Norm-based generalisation bounds for multi-class convolutional neural networks cs.LG · 2019 · author #4
  50. Scalable Generalized Dynamic Topic Models stat.ML · 2018 · author #3
  51. Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation stat.ML · 2018 · author #4
  52. Bayesian Nonlinear Support Vector Machines for Big Data stat.ML · 2017 · author #4
  53. Data-dependent Generalization Bounds for Multi-class Classification cs.LG · 2017 · author #4
  54. Distributed Optimization of Multi-Class SVMs stat.ML · 2016 · author #4
  55. Feature Importance Measure for Non-linear Learning Algorithms cs.AI · 2016 · author #4
  56. Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning cs.LG · 2016 · author #3
  57. Sparse Probit Linear Mixed Model stat.ML · 2015 · author #6
  58. Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis stat.ML · 2015 · author #2
  59. Localized Multiple Kernel Learning---A Convex Approach cs.LG · 2015 · author #4
  60. Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms cs.LG · 2015 · author #4
  61. Probabilistic Clustering of Time-Evolving Distance Data cs.LG · 2015 · author #2
  62. Localized Complexities for Transductive Learning stat.ML · 2014 · author #3
  63. Insights from Classifying Visual Concepts with Multiple Kernel Learning cs.CV · 2011 · author #3
  64. The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning stat.ML · 2011 · author #1
  65. A Unifying View of Multiple Kernel Learning stat.ML · 2010 · author #1
  66. Non-Sparse Regularization for Multiple Kernel Learning cs.LG · 2010 · author #1
  67. Security Analysis of Online Centroid Anomaly Detection stat.ML · 2010 · author #1

Mentions

  • 2508.16235 #4 · arxiv_oai · confidence 0.70 Marius Kloft
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Frequent Coauthors