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Research facility · Berlin · ??

Berlin Institute for the Foundations of Learning and Data

bifold.berlinROR OpenAlex
Research works
38
fractional, all time
Citations
1.2k
32.3 per fractional work
Top-10% rate
39.6%
record average 16.5%
Open access
78%
world 28%

Not ranked overall: Berlin Institute for the Foundations of Learning and Data is under the volume floor below which an excellence rate is noise. Not ranked is not the same as ranked last.

Field profile

Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.

Biochemistry, Genetics and Molecular Biology: 1.47× its world share, 2 worksBiochemistry, Geneti…Immunology and Microbiology: 0.26× its world share, 0 worksImmunology and Micro…Neuroscience: 4.28× its world share, 2 worksNeuroscienceChemical Engineering: 1.85× its world share, 0 worksChemical EngineeringChemistry: 1.33× its world share, 1 worksChemistryComputer Science: 5.36× its world share, 13 worksComputer ScienceEarth and Planetary Sciences: 0.80× its world share, 0 worksEarth and Planetary …Engineering: 0.61× its world share, 3 worksEngineeringEnvironmental Science: 0.23× its world share, 0 worksEnvironmental ScienceMaterials Science: 2.45× its world share, 3 worksMaterials ScienceMathematics: 1.29× its world share, 0 worksMathematicsPhysics and Astronomy: 1.80× its world share, 1 worksPhysics and AstronomyHealth Professions: 0.03× its world share, 0 worksHealth ProfessionsMedicine: 0.49× its world share, 3 worksMedicineArts and Humanities: 0.21× its world share, 0 worksArts and HumanitiesDecision Sciences: 1.65× its world share, 0 worksDecision SciencesEconomics, Econometrics and Finance: 0.88× its world share, 1 worksEconomics, Econometr…Psychology: 0.08× its world share, 0 worksPsychologySocial Sciences: 0.08× its world share, 0 worksSocial Sciences1×world share
more than its size predictsabout as predictedless

Rings at 0.5×, 1× and 2×. Widest outward: Computer Science, 5.4×. Every wedge is a field page.

Which keywords describe research at Berlin Institute for the Foundations of Learning and Data?

By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Machine Learning, Deep Neural Networks, Data Mining, Neural Networks, Interpretable Models, Machine Learning Interpretability and Feature Extraction.

▲ more of its work than of the world’s◆ about the world’s share▼ less than the world’s

Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 27 words are chosen for being large and distinctive. Each links to the topic it comes from most.

All 27 words, with their numbers
  1. Deep Learning8▲ 7.6×34 topics
  2. Machine Learning7▲ 7.1×28 topics
  3. Deep Neural Networks3▲ 87×3 topics
  4. Neural Networks3▲ 5.9×12 topics
  5. Data Mining3▲ 11×4 topics
  6. Interpretable Models2▲ 177×1 topic
  7. Machine Learning Interpretability2▲ 177×1 topic
  8. Feature Extraction2▲ 15×6 topics
  9. Molecular Dynamics2▲ 42×3 topics
  10. Classification2▲ 14×4 topics
  11. Computational Chemistry2▲ 76×2 topics
  12. High-Throughput2▲ 105×1 topic
  13. Materials Informatics2▲ 105×1 topic
  14. Remote Sensing2▲ 4.1×4 topics
  15. Convolutional Neural Networks1▲ 6.0×7 topics
  16. Medical Imaging1▲ 8.5×5 topics
  17. Meta-Learning1▲ 51×2 topics
  18. Precision Medicine1▲ 8.8×5 topics
  19. Support Vector Machines1▲ 13×3 topics
  20. Change Detection1▲ 57×2 topics
  21. Hyperspectral1▲ 40×1 topic
  22. Image Analysis1▲ 37×2 topics
  23. Spectral Unmixing1▲ 69×1 topic
  24. Transfer Learning1▲ 17×3 topics
  25. Healthcare1▲ 2.9×4 topics
  26. Representation Learning1▲ 24×2 topics
  27. Unsupervised Learning1▲ 23×2 topics

Which research topics does Berlin Institute for the Foundations of Learning and Data publish most on?

By volume in 2022–2025: Explainable Artificial Intelligence (XAI), Machine Learning in Materials Science, Remote-Sensing Image Classification and Privacy-Preserving Technologies in Data.

Explainable Artificial I…2Explainable Artificial Intelligence (XAI): 2 fractional worksMachine Learning in Materials Science: 2 fractional worksRemote-Sensing Image Classification: 1 fractional worksPrivacy-Preserving Technologies in Data: 1 fractional worksDomain Adaptation and Few-Shot Learning: 1 fractional worksEEG and Brain-Computer Interfaces: 1 fractional worksMachine Learning and Data Classification: 1 fractional worksCancer Genomics and Diagnostics: 0 fractional worksArtificial Intelligence in Healthcare and Education: 0 fractional worksAnomaly Detection Techniques and Applications: 0 fractional works
Artificial IntelligenceMaterials ChemistryMedia TechnologyCognitive Neuroscience2 others

Area is fractional works; colour is the subfield each topic belongs to.

  1. 1 Explainable Artificial Intelligence (XAI) Artificial Intelligence 2 works
  2. 2 Machine Learning in Materials Science Materials Chemistry 2 works
  3. 3 Remote-Sensing Image Classification Media Technology 1 works
  4. 4 Privacy-Preserving Technologies in Data Artificial Intelligence 1 works
  5. 5 Domain Adaptation and Few-Shot Learning Artificial Intelligence 1 works
  6. 6 EEG and Brain-Computer Interfaces Cognitive Neuroscience 1 works
  7. 7 Machine Learning and Data Classification Artificial Intelligence 1 works
  8. 8 Cancer Genomics and Diagnostics Cancer Research 0 works
  9. 9 Artificial Intelligence in Healthcare and Education Health Informatics 0 works
  10. 10 Anomaly Detection Techniques and Applications Artificial Intelligence 0 works

How open and international is its research?

Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.

openly available78.4%not open21.6%

World: 28% of research is openly available.

with international co-authors64.9%domestic only35.1%

World: 19% is written across borders.

How has Berlin Institute for the Foundations of Learning and Data's research output changed?

grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Other research institutions in Berlin

All research institutions in Berlin

Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.