Tootfinder

Morgen dus waarschijnlijk de hele dag een van de debatten die de meeste aandacht zal krijgen, maar inhoudelijk totaal niets waard hoogst waarschijnlijk.
@… #politiek #debat

Various irrational series involving binomial coefficients
Zhi-Wei Sun
https://arxiv.org/abs/2506.01870 https://arxiv.org/pdf/2506.018…

Various irrational series involving binomial coefficients
Motivated by Galois theory, we propose some new irrational series of Ramanujan's type or Zeilberger's type. For example, we conjecture that \begin{equation*}\sum_{k=1}^\infty\frac{\binom{2k}k^2\binom{4k}{2k}}{(84-32\sqrt6)^{4k}} \left(280k+5\sqrt6+26\right)=\frac3π(2\sqrt3+33\sqrt2) \end{equation*} and \begin{align*}&\sum_{k=1}^\infty\frac{(27(37102-15147\sqrt6))^k}{k^3\binom{2k}k^2\binom{3k}k} \left(9k(11\sqrt6+51)-2(19\sqrt6+54)\right) \\&\qquad=\frac{5625}2\left(\sqrt6 L_{-24}(2)-3G\r…

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Zhao Mandi, Yifan Hou, Dieter Fox, Yashraj Narang, Ajay Mandlekar, Shuran Song
https://arxiv.org/abs/2505.24853

DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
We study the problem of functional retargeting: learning dexterous manipulation policies to track object states from human hand-object demonstrations. We focus on long-horizon, bimanual tasks with articulated objects, which is challenging due to large action space, spatiotemporal discontinuities, and embodiment gap between human and robot hands. We propose DexMachina, a novel curriculum-based algorithm: the key idea is to use virtual object controllers with decaying strength: an object is first…

Concentration of the maximum size of an induced subtree in moderately sparse random graphs
J. C. Buitrago Oropeza
https://arxiv.org/abs/2506.02801 https://…

Concentration of the maximum size of an induced subtree in moderately sparse random graphs
Kamaldinov, Skorkin, and Zhukovskii proved that the maximum size of an induced subtree in the binomial random graph $G(n,p)$ is concentrated at two consecutive points, whenever $p\in(0,1)$ is a constant. Using improved bounds on the second moment of the number of induced subtrees, we show that the same result holds when $n^{-\frac{e-2}{3e-2}+\varepsilon}\leq p=o(1)$.

Bi-Manual Joint Camera Calibration and Scene Representation
Haozhan Tang, Tianyi Zhang, Matthew Johnson-Roberson, Weiming Zhi
https://arxiv.org/abs/2505.24819

Bi-Manual Joint Camera Calibration and Scene Representation
Robot manipulation, especially bimanual manipulation, often requires setting up multiple cameras on multiple robot manipulators. Before robot manipulators can generate motion or even build representations of their environments, the cameras rigidly mounted to the robot need to be calibrated. Camera calibration is a cumbersome process involving collecting a set of images, with each capturing a pre-determined marker. In this work, we introduce the Bi-Manual Joint Calibration and Representation Fra…

Boosting Binomial Exotic Option Pricing with Tensor Networks
Maarten van Damme, Rishi Sreedhar, Martin Ganahl
https://arxiv.org/abs/2505.17033 https://

Boosting Binomial Exotic Option Pricing with Tensor Networks
Pricing of exotic financial derivatives, such as Asian and multi-asset American basket options, poses significant challenges for standard numerical methods such as binomial trees or Monte Carlo methods. While the former often scales exponentially with the parameters of interest, the latter often requires expensive simulations to obtain sufficient statistical convergence. This work combines the binomial pricing method for options with tensor network techniques, specifically Matrix Product States…

Bulls vs Bears: a Trinomial Model of a Financial Asset
Nahuel I. Arca
https://arxiv.org/abs/2505.18723 https://arxiv.org/pdf/2505.187…

Bulls vs Bears: a Trinomial Model of a Financial Asset
We present a variation of the well-known binomial model of asset prices. This variation incorporates a bound to short-selling, inspired by a model from Gunduz Caginalp[2]. We formalize this model and prove a formula for all the moments of the logarithmic returns. We also derive a formula for the case with infinitely many investors. As an application of the model, we show how to compute parameters in order to approximate given moments, enabling the modeling of skewness and excess kurtosis. Final…