Titlebook: Mathematics of Program Construction; 14th International C Ekaterina Komendantskaya Conference proceedings 2022 The Editor(s) (if applicable

抗體

N防腐劑

,Folding over?Neural Networks,n scheme patterns. In turn, we promote a coherent implementation of neural networks that delineates between their structure and semantics, allowing for compositionality in both how they are built and how they are trained.

Osteons

玉米

不適

Fluctuate

SIT

Subtyping Without Reduction,ticle, we show how operations on a subtype can be represented in a more efficient manner that exhibits no reduction behaviour. We present the general form of the technique in Cubical Agda by exploiting its support by higher-inductive types, and demonstrate the practical use of the technique with a number of examples.

exclusice

Calculating Datastructures,aws relating types and arithmetic. Although these calculations do not generally produce novel datastructures they do give insight into how certain datastructures arise and how different implementations are related.

NICHE

,Breadth-First Traversal via?Staging,Depth-first effectful traversal of a tree is straightforward to define compositionally, since it precisely follows the shape of the data. What about breadth-first effectful traversal? An indirect route is to factorize the data structure into shape and contents, traverse the contents, then rebuild th

過(guò)時(shí)

Subtyping Without Reduction, gives no control over when the reduction of subtyping proofs takes place, which can significantly impact the performance of type-checking. In this article, we show how operations on a subtype can be represented in a more efficient manner that exhibits no reduction behaviour. We present the general