Scale-Invariant Error

$$$$D(y, y__star) == frac(1 * 2 * n) * sum((log(y_i - log(y_i__star

+ alpha(y, y__star)))))

Multi-scale CRFs

$$$$def expectation(l):

N=10000

return mean(l() for _ in range(N))

P(d / s_hat) == 1/Z(s_hat) * exp(- expectation(lambda: (d, s_hat)

))

Multi-scale CRFs

$$$$phi(d_i**l, s_hat) ==(d_i**l - s_i**l)**2

Scale-Invariant Error

$$$$D(y, y__star) == frac(1 * 2 * n) * sum((log(y_i - log(y_i__star

+ alpha(y, y__star)))))

Multi-scale CRFs

$$$$def expectation(l):

N=10000

return mean(l() for _ in range(N))

P(d / s_hat) == 1/Z(s_hat) * exp(- expectation(lambda: (d, s_hat)

))

Multi-scale CRFs

$$$$phi(d_i**l, s_hat) ==(d_i**l - s_i**l)**2

Scale-Invariant Error

$$$$D(y, y__star) == frac(1 * 2 * n) * sum((log(y_i - log(y_i__star

+ alpha(y, y__star)))))

Multi-scale CRFs

$$$$def expectation(l):

N=10000

return mean(l() for _ in range(N))

P(d / s_hat) == 1/Z(s_hat) * exp(- expectation(lambda: (d, s_hat)

))

Multi-scale CRFs

$$$$phi(d_i**l, s_hat) ==(d_i**l - s_i**l)**2

Scale-Invariant Error

$$$$D(y, y__star) == frac(1 * 2 * n) * sum((log(y_i - log(y_i__star

+ alpha(y, y__star)))))

Multi-scale CRFs

$$$$def expectation(l):

N=10000

return mean(l() for _ in range(N))

P(d / s_hat) == 1/Z(s_hat) * exp(- expectation(lambda: (d, s_hat)

))

Multi-scale CRFs

$$$$phi(d_i**l, s_hat) ==(d_i**l - s_i**l)**2