181 results on '"Alexander Gepperth"'
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2. An analysis of best-practice strategies for replay and rehearsal in continual learning.
3. Continual Reinforcement Learning Without Replay Buffers.
4. Enhancing the Robustness of Model-Predictive Control using GMMs as Outlier Detection.
5. Adiabatic replay for continual learning.
6. Safe contextual Bayesian optimization integrated in industrial control for self-learning machines.
7. Continual Learning of Deep Neural Networks in The Age of Big Data.
8. Free-Hand Gesture Recognition Using Conv3D-Networks with Cross Stitch Units for Multi-Modal Data.
9. Continual Learning: Applications and the Road Forward.
10. Gesture Recognition and Multi-modal Fusion on a New Hand Gesture Dataset.
11. Gesture Recognition on a New Multi-Modal Hand Gesture Dataset.
12. Gesture MNIST: A New Free-Hand Gesture Dataset.
13. A Study of Continual Learning Methods for Q-Learning.
14. Large-scale gradient-based training of Mixtures of Factor Analyzers.
15. A new perspective on probabilistic image modeling.
16. Adiabatic replay for continual learning.
17. Large-scale gradient-based training of Mixtures of Factor Analyzers.
18. On the improvement of model-predictive controllers.
19. Continual Learning: Applications and the Road Forward.
20. Multi-Pronged Safe Bayesian Optimization for High Dimensions.
21. An Investigation of Replay-based Approaches for Continual Learning.
22. Image Modeling with Deep Convolutional Gaussian Mixture Models.
23. Overcoming Catastrophic Forgetting with Gaussian Mixture Replay.
24. An empirical comparison of generators in replay-based continual learning.
25. Tutorial - Continual Learning beyond classification.
26. On Multi-modal Fusion for Freehand Gesture Recognition.
27. A Rigorous Link Between Self-Organizing Maps and Gaussian Mixture Models.
28. A Survey of Machine Learning applied to Computer Networks.
29. SASBO: Self-Adapting Safe Bayesian Optimization.
30. Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data.
31. Beyond Supervised Continual Learning: a Review.
32. A Study of Deep Learning for Network Traffic Data Forecasting.
33. A Study on Catastrophic Forgetting in Deep LSTM Networks.
34. Marginal Replay vs Conditional Replay for Continual Learning.
35. Simplified Computation and Interpretation of Fisher Matrices in Incremental Learning with Deep Neural Networks.
36. Robustness of Deep LSTM Networks in Freehand Gesture Recognition.
37. Flow-based Throughput Prediction using Deep Learning and Real-World Network Traffic.
38. Incremental learning with a homeostatic self-organizing neural model.
39. An energy-based SOM model not requiring periodic boundary conditions.
40. Predicting Network Flow Characteristics Using Deep Learning and Real-World Network Traffic.
41. Catastrophic Forgetting: Still a Problem for DNNs.
42. An Energy-Based Convolutional SOM Model with Self-adaptation Capabilities.
43. Continual Learning with Fully Probabilistic Models.
44. An energy-based SOM model not requiring periodic boundary conditions.
45. Incremental learning with self-organizing maps.
46. Dynamic Hand Gesture Recognition for Mobile Systems Using Deep LSTM.
47. Free-hand gesture recognition with 3D-CNNs for in-car infotainment control in real-time.
48. A large-scale multi-pose 3D-RGB object database.
49. A comprehensive, application-oriented study of catastrophic forgetting in DNNs.
50. A Deep Learning Approach for Hand Posture Recognition from Depth Data.
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