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Žiga Sajovic

Publications and source records attributed to Žiga Sajovic.

3 recordsLinked to original sources

trueform: Fast And Robust Mesh CSG Via Topological Aggregation

Mesh CSG output is consumed in floating point: however exact the computation, every emitted coordinate is materialised -- rounded to a representable position -- and the next stage can observe crossings and orderings the exact result never had. Only index-based topology survives materialisation. We keep it exact: within the build, the arrangement's radial structure is ordered by exact predicates on the original input planes -- exact without exact constructions -- and where a decision spans faces, the intended answer is recovered by topological aggregation: a majority vote over the disagreeing geometric observations within their topological unit. We compute the arrangement locally with integer-exact predicates, every stage a graph problem on graphs it never explicitly constructs. Pairwise intersections are classified into five canonical types (VV, VE, VF, EE, EF), each cut face is arranged in its own plane, and a two-level identity keeps the result consistent across faces with no global structure. The arrangement and its domain partition are built once and queried arbitrarily often: a boolean of any arity is a per-domain bit test, volumetric regions read straight off the partition, and open surfaces -- declared as oriented sheets -- cut volumes through the same algebra. The method is implemented in the header-only trueform library, in C++ with Python and TypeScript bindings. Compared to prior art, it produces valid, watertight output while running up to two orders of magnitude faster, and stays interactive in the browser.

cs.CG↗

Operational Calculus for Differentiable Programming

In this work we present a theoretical model for differentiable programming. We construct an algebraic language that encapsulates formal semantics of differentiable programs by way of Operational Calculus. The algebraic nature of Operational Calculus can alter the properties of the programs that are expressed within the language and transform them into their solutions. In our model programs are elements of programming spaces and viewed as maps from the virtual memory space to itself. Virtual memory space is an algebra of programs, an algebraic data structure one can calculate with. We define the operator of differentiation ($\partial$) on programming spaces and, using its powers, implement the general shift operator and the operator of program composition. We provide the formula for the expansion of a differentiable program into an infinite tensor series in terms of the powers of $\partial$. We express the operator of program composition in terms of the generalized shift operator and $\partial$, which implements a differentiable composition in the language. Such operators serve as abstractions over the tensor series algebra, as main actors in our language. We demonstrate our models usefulness in differentiable programming by using it to analyse iterators, deriving fractional iterations and their iterating velocities, and explicitly solve the special case of ReduceSum.

cs.FL↗

Automatic Differentiation: a look through Tensor and Operational Calculus

In this paper we take a look at Automatic Differentiation through the eyes of Tensor and Operational Calculus. This work is best consumed as supplementary material for learning tensor and operational calculus by those already familiar with automatic differentiation. To that purpose, we provide a simple implementation of automatic differentiation, where the steps taken are explained in the language tensor and operational calculus.

cs.SC↗