Tootfinder

This https://arxiv.org/abs/2412.06481 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization
This paper introduces Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization (DeePC-Hunt), a backpropagation-based method for automatic hyperparameter tuning of the DeePC algorithm. The necessity for such a method arises from the importance of hyperparameter selection to achieve satisfactory closed-loop DeePC performance. The standard methods for hyperparameter selection are to either optimize the open-loop performance, or use manual guess-and-check. Optimizing th…

This https://arxiv.org/abs/2412.06481 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization
This paper introduces Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization (DeePC-Hunt), a backpropagation-based method for automatic hyperparameter tuning of the DeePC algorithm. The necessity for such a method arises from the importance of hyperparameter selection to achieve satisfactory closed-loop DeePC performance. The standard methods for hyperparameter selection are to either optimize the open-loop performance, or use manual guess-and-check. Optimizing th…

Det gik ellers lige så godt, men så viste det sig at være en ommer 😄

Volume Entropy Rigidity for Random Groups at Low Densities
Dongming Hua (Merrick)
https://arxiv.org/abs/2505.23364 https://arxiv.org/…

Volume Entropy Rigidity for Random Groups at Low Densities
We study the rigidity of the volume entropy for weighted word metrics on hyperbolic groups, building on a recent convexity result due to Cantrell-Tanaka. Using ideas from small cancellation theory, we give conditions under which a hyperbolic group admits a unique normalized weight minimizing the entropy. Moreover, we show that these conditions are generic for random groups at small densities, and that the unique minimizer of such a generic group is arbitrarily close to the uniform weight.

This https://arxiv.org/abs/2412.17410 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Rigidity of spacelike hypersurface with constant curvature and intersection angle condition
In the Minkowski space, we consider a spacelike hypersurface with boundary, which can be written as a graph on a spacelike hyperplane. We prove that, if its $k$-th mean curvature is constant, and its boundary is on the hyperplane with constant intersection angles, then the hypersurface must be a part of a hyperboloid, unless it is entirely contained in the hyperplane. This result can be seen as an analog of the sphere theorem for the hypersurface of constant $k$-th mean curvature in the Euclide…

This https://arxiv.org/abs/2210.07029 has been replaced.
link: https://scholar.google.com/scholar?q=a

The fractional $p$-Laplacian on hyperbolic spaces
We present three equivalent definitions of the fractional $p$-Laplacian $(-Δ_{\mathbb{H}^{n}})^{s}_{p}$, $01$, with normalizing constants, on hyperbolic spaces. The explicit values of the constants enable us to study the convergence of the fractional $p$-Laplacian to the $p$-Laplacian as $s \to 1^{-}$.

This https://arxiv.org/abs/2502.06044 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Scalable Differentially Private Bayesian Optimization
In recent years, there has been much work on scaling Bayesian Optimization to high-dimensional problems, for example hyperparameter tuning in large machine learning models. These scalable methods have been successful, finding high objective values much more quickly than traditional global Bayesian Optimization or random search-based methods. At the same time, these large models often use sensitive data, but preservation of Differential Privacy has not scaled alongside these modern Bayesian Opti…

This https://arxiv.org/abs/2410.03614 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Proudfoot-Speyer degenerations of scattering equations
We study scattering equations of hyperplane arrangements from the perspective of combinatorial commutative algebra and numerical algebraic geometry. We formulate the problem as linear equations on a reciprocal linear space and develop a degeneration-based homotopy algorithm for solving them. We investigate the Hilbert regularity of the corresponding homogeneous ideal and apply our methods to CHY scattering equations.

Assembly in Directed Hypergraphs
Christoph Flamm, Daniel Merkle, Peter F. Stadler
https://arxiv.org/abs/2505.22826 https://arxiv.org/…

Assembly in Directed Hypergraphs
Assembly theory has received considerable attention in the recent past. Here we analyze the formal framework of this model and show that assembly pathways coincide with certain minimal hyperpaths in B-hypergraphs. This makes it possible to generalize the notion of assembly to general chemical reaction systems and to make explicit the connection to rule based models of chemistry, in particular DPO graph rewriting. We observe, furthermore, that assembly theory is closely related to retrosynthetic…

Hyperbolic Monge-Amp\`ere systems with $S_1=0$
Yuhao Hu
https://arxiv.org/abs/2505.21998 https://arxiv.org/pdf/2505.21998

Hyperbolic Monge-Ampère systems with $S_1=0$
For hyperbolic Monge-Ampère systems, a well-known solution of the equivalence problem yields two invariant tensors, ${S}_1$ and ${S}_2$, defined on the underlying $5$-manifold, where ${S}_2=0$ characterizes systems that are Euler-Lagrange. In this article, we consider the `opposite' case, ${S}_1 = 0$, and show that the local generality of such systems is `$2$ arbitrary functions of $3$ variables'. In addition, we classify all $S_1=0$ systems with cohomogeneity at most one, which turn out to be…