This paper presents an algorithmic framework for exhaustively generating and tabulating knot and link diagrams on the thickened torus.

The paper introduces an integrated computational toolbox using topological and fractal analysis to quantitatively track microstructural changes during casein gelation, correlating these subtle changes…

The paper introduces Cellular Sheaf Neural Operators, a discretization-aware framework that models constrained PDEs by representing physical states on oriented cell complexes to enforce structure-pres…

The paper introduces a computational framework using Hodge zero-modes to track the geometry of topological features in parameter-dependent data, providing metrics like curvature and holonomy to quanti…

The paper validates a specialized mathematical metric (the Burau-Lyapunov exponent) designed for detecting privilege escalation in cloud IAM graphs by applying it to an unrelated physical system: sola…

The paper introduces a subgrid marching tetrahedra scheme that accurately recovers complex, intersection-free manifold meshes from tetrahedral grids, overcoming limitations of classic marching methods…

The paper proposes ZK-Flex, a flexible software-hardware co-designed framework that significantly accelerates Zero-Knowledge Proof (ZKP) generation by efficiently handling diverse polynomial and ellip…

The paper proposes ZK-Flex, a flexible software-hardware co-designed framework that significantly accelerates Zero-Knowledge Proof (ZKP) generation by efficiently handling diverse polynomial and ellip…

This paper introduces a robust magneto-thermal surface contact approximation (SCA) that efficiently models the electrical and thermal behavior of turn-to-turn contact layers in no-insulation HTS coils…

The paper introduces Singularity-aware Adam (S-Adam), a novel optimizer that stabilizes deep learning training in non-smooth loss landscapes by dynamically damping updates based on local geometric ins…

The paper introduces the EXTRA homogenization method, which enables accurate and computationally efficient 3D magneto-thermal finite-element simulation of large-scale HTS magnets by selectively resolv…

This paper proposes a two-stage method to improve the efficiency and robustness of the Locally Aligned Ant Technique (LAAT) for detecting cosmic structures in noisy, high-dimensional point clouds.

The paper demonstrates that enforcing a local conservative finite volume structure is crucial for achieving stable, accurate long-term autoregressive rollouts of plasma transport simulations, outperfo…

The paper introduces BOUNDARY FLOW, an LLVM-based framework that enhances kernel fuzzing and analysis by extracting per-task, state-aware data-flow information (arguments and return values) at functio…

The paper proposes a novel multimodal learning approach to predict the properties of new bilayer 2D materials formed by stacking dissimilar functional layers.

The paper introduces a novel padding method that leverages crystal symmetry to enhance the encoding of complex inorganic structures, significantly improving the generation of stable, novel materials.

The paper introduces performance ruggedness analysis to quantify performance variance in GEMM workloads, proposing a two-stage software stack that significantly smooths the performance landscape and b…

The paper proves the real-rootedness and ultra-log-concavity of the Poincaré polynomials for the moduli space $\overline{\mathcal M}_{0,n}$ and the Fulton--MacPherson space $\mathbb{P}^1[n]$ using a n…

The paper introduces MORPH, a framework that reformulates Zero-Knowledge Proof (ZKP) computations to efficiently utilize AI ASICs like TPUs, achieving up to 10x higher throughput on NTT.

This paper presents Mana, a sim-to-real framework for dexterous articulated tool manipulation.