R. T. Ten Haken
Radiology, Nuclear Medicine and Imaging · 2002–2017
A researcher in the Science corpus: 6 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Radiology, Nuclear Medicine and Imaging — 23 citations into it
- Biomedical Engineering — 9 citations into it
Whom R. T. Ten Haken trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from R. T. Ten Haken's perspective
Ordered by how strongly the researchers R. T. Ten Haken trusts endorse each paper. Same corpus, a different order for every researcher.
- Dropout: a simple way to prevent neural networks from overfitting
- Human-level control through deep reinforcement learning
- GENERATIVE ADVERSARIAL NETS
- Playing Atari with Deep Reinforcement Learning (arXiv.org)
- Deep Learning
- Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
- The Nature of Statistical Learning Theory
- Multilayer feedforward networks are universal approximators
- Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
- An Analysis of Temporal-Difference Learning with Function Approximation
Their papers
- Unraveling Biophysical Interactions of Radiation Pneumonitis in Non-Small-Cell Lung Cancer via Bayesian Network Analysis (2017) — 57 citations
- Deep Reinforcement Learning for Automated Radiation Adaptation in Lung Cancer (2017) — 241 citations
- Radiogenomics and Radiotherapy Response Modeling (2017) — 52 citations
- Effect of Midtreatment PET/CT-Adapted Radiation Therapy With Concurrent Chemotherapy in Patients With Locally Advanced Non–Small-Cell Lung Cancer (2017) — 197 citations
- The Use of Normal Tissue Complication Probability (NTCP) Models in the Clinic (2010) — 1,722 citations
- Analysis of radiation-induced liver disease using the Lyman NTCP model. (2002) — 721 citations