- In mathematics,
equivariance is a form of
symmetry for
functions from one
space with
symmetry to
another (such as
symmetric spaces). A
function is said...
- when K{\displaystyle \mathbb {K} } has
characteristic zero,
since shift-
equivariance is a
fairly strong condition. The
forward difference operator...
- methods. See
invariant estimator for
background on
invariance or see
equivariance. For any a>0{\displaystyle a>0} and τ∈[0,1]{\displaystyle \tau \in [0...
- Rg{\displaystyle R_{g}}
taking the
horizontal subspaces into each other. This
equivariance of the
horizontal subspaces H⊂TP{\displaystyle H\subset TP} interpreted...
- In
mathematics (in particular,
functional analysis),
convolution is a
mathematical operation on two
functions ( f {\displaystyle f} and g {\displaystyle...
- _{i}=h_{i}(\theta _{1},\theta _{2},\ldots ,\theta _{k})~.}
Because of the
equivariance of the
maximum likelihood estimator, the
properties of the MLE apply...
- of
input features in the
visual field, i.e. they
grant translational equivariance -
given that the
layer has a
stride of one. Pooling: In a CNN's pooling...
-
sections of a Poincaré-equivariant
vector bundle over
Minkowski space. The
equivariance condition means that the
group acts on the
total space of the vector...
-
permuting weight matrices of the network. This
property is
known as
equivariance to
permutation of deep
weight spaces. Sometimes,
parameters are analyzed...
- {\displaystyle \rho } is an
equivariant map T : F → W {\displaystyle T:F\to W} .
Equivariance here
means that T ( F R ) = ρ ( R − 1 ) T ( F ) . {\displaystyle T(FR)=\rho...
