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Differential geometry and stochastic dynamics with deep learning numerics
Line Kühnel
*
,
Stefan Sommer
, Alexis Arnaudon
*
Corresponding author for this work
Department of Computer Science
5
Citations (Scopus)
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Mathematics
Applied mathematics
29%
Automatic Differentiation
40%
Concepts
14%
Curvature
21%
Data analysis
25%
Demonstrate
33%
Derivative
17%
Differential Geometry
86%
Flexibility
26%
Framework
47%
Geodesic
24%
Group Theory
28%
High Performance
36%
High-dimensional
22%
Invariance
24%
Learning
75%
Libraries
30%
Line
18%
Metric
18%
Numerical Computation
54%
Numerics
91%
Python
40%
Scaling
23%
Simplicity
26%
Statistics
19%
Stochastic Dynamics
100%
Symbolic Computation
31%
Visualization
30%
Engineering & Materials Science
Computational methods
17%
Deep learning
74%
Derivatives
13%
Geometry
50%
Group theory
25%
Invariance
17%
Lie groups
24%
Statistics
12%
Visualization
12%