An anomaly detection apparatus comprising a recording unit adapted to record a parameter θ of a second probability distribution q 2 (x;θ), an anomaly degree estimating unit adapted to estimate an anomaly degree indicating a degree of anomaly of anomaly detection target equipment from a sound emitted from the anomaly detection target equipment, hereinafter referred to as anomaly detection target sound, based on the second probability distribution q 2 (x;θ), and an anomaly degree determining unit adapted to generate a determination result indicating whether or not the anomaly detection target equipment is abnormal from the anomaly degree, characterized in that the second probability distribution q 2 (x;θ) is a probability distribution indicating a distribution of a normal sound emitted from the anomaly detection target equipment, which is obtained by updating a first probability distribution indicating a distribution of a normal sound emitted from one or more pieces of equipment of the same type as the anomaly detection target equipment and different from the anomaly detection target equipment, using the normal sound emitted from the anomaly detection target equipment, hereinafter referred to as normal sound for adaptive learning, wherein a variable x of the second probability distribution q 2 (x;θ) is a variable indicating input data generated from the normal sound emitted from the anomaly detection target equipment, the variable x is expressed as x = f K (f K-1 (...(f 1 (z 0))...)) using transformations f i (i = 1,..., K, K is an integer of 1 or greater, and inverse transformations f i -1 exist for the transformations f i) and a latent variable z 0, q 0 (z 0) is set as a probability distribution of the latent variable z 0, and the probability distribution q 2 (x;θ) of the input data x is calculated using the probability distribution q 0 (z 0) of the latent variable z 0 = f 1 -1 (f 2 -1 (...(f K -1 (x))...)) corresponding to the input data x. a recording unit adapted to record a parameter θ of a second probability distribution q 2 (x;θ), an anomaly degree estimating unit adapted to estimate an anomaly degree indicating a degree of anomaly of anomaly detection target equipment from a sound emitted from the anomaly detection target equipment, hereinafter referred to as anomaly detection target sound, based on the second probability distribution q 2 (x;θ), and an anomaly degree determining unit adapted to generate a determination result indicating whether or not the anomaly detection target equipment is abnormal from the anomaly degree, characterized in that the second probability distribution q 2 (x;θ) is a probability distribution indicating a distribution of a normal sound emitted from the anomaly detection target equipment, which is obtained by updating a first probability distribution indicating a distribution of a normal sound emitted from one or more pieces of equipment of the same type as the anomaly detection target equipment and different from the anomaly detection target equipment, using the normal sound emitted from the anomaly detection target equipment, hereinafter referred to as normal sound for adaptive learning, wherein a variable x of the second probability distribution q 2 (x;θ) is a variable indicating input data generated from the normal sound emitted from the anomaly detection target equipment, the variable x is expressed as x = f K (f K-1 (...(f 1 (z 0))...)) using transformations f i (i = 1,..., K, K is an integer of 1 or greater, and inverse transformations f i -1 exist for the transformations f i) and a latent variable z 0, q 0 (z 0) is set as a probability distribution of the latent variable z 0, and the probability distribution q 2 (x;θ) of the input data x is calculated using the probability distribution q 0 (z 0) of the latent variable z 0 = f 1 -1 (f 2 -1 (...(f K -1 (x))...)) corresponding to the input data x.