no code implementations • 26 Jul 2024 • Liangjie Sun, Wai-Ki Ching, Tatsuya Akutsu
In this paper, we mainly focus on three types of BNs with $n$ nodes (i. e., $K$-AND-OR-BNs, $K$-XOR-BNs, and $K$-NC-BNs, where $K$ is the number of input nodes for each node and NC means nested canalyzing) and study the upper and lower bounds of the number of observation nodes for these BNs.
1 code implementation • 16 Jul 2024 • Christopher H. Fok, Chi-Wing Wong, Wai-Ki Ching
We derive theoretical upper bounds for both existing algorithms and the GER algorithm.
no code implementations • 21 Apr 2020 • Avraham A. Melkman, Sini Guo, Wai-Ki Ching, Pengyu Liu, Tatsuya Akutsu
An autoencoder is a layered neural network whose structure can be viewed as consisting of an encoder, which compresses an input vector of dimension $D$ to a vector of low dimension $d$, and a decoder which transforms the low-dimensional vector back to the original input vector (or one that is very similar).
