Tootfinder

Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning
Bastien Dubail, Stefan Stojanovic, Alexandre Prouti\`ere
https://arxiv.org/abs/2509.05193 htt…

Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning
Low-rank structure is a common implicit assumption in many modern reinforcement learning (RL) algorithms. For instance, reward-free and goal-conditioned RL methods often presume that the successor measure admits a low-rank representation. In this work, we challenge this assumption by first remarking that the successor measure itself is not low-rank. Instead, we demonstrate that a low-rank structure naturally emerges in the shifted successor measure, which captures the system dynamics after bypa…

Weakly Strongly 2-Nil-Clean Rings
Peter Danchev, Mina Doostalizadeh, Ahmad Moussavi
https://arxiv.org/abs/2509.05673 https://arxiv.org/pdf/2509.05673

Weakly Strongly 2-Nil-Clean Rings
In this paper, we introduce and explore in-depth the notion of {\it weakly strongly 2-nil-clean rings} as a common non-trivial generalization of both strongly 2-nil-clean rings and strongly weakly nil-clean rings as defined and studied by Chen-Sheibani in the J. Algebra \& Appl. (2017). We, specifically, succeeded to prove that any weakly strongly 2-nil-clean ring is strongly $π$-regular and, concretely, it decomposes as the direct product of a strongly 2-nil-clean ring and a ring of the type …

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation
Runshi Tang, Runbing Zheng, Anru R. Zhang, Carey E. Priebe
https://arxiv.org/abs/2509.05221

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation
Dynamic multilayer networks are frequently used to describe the structure and temporal evolution of multiple relationships among common entities, with applications in fields such as sociology, economics, and neuroscience. However, exploration of analytical methods for these complex data structures remains limited. We propose a functional tensor-based model for dynamic multilayer networks, with the key feature of capturing the shared structure among common vertices across all layers, while simul…

Apropos of nothing, AR-15s fire little bullets that can be thrown around by the wind. They're basically high velocity 22s, which makes them garbage for accuracy at range. Snipers use big heavy ammo like 30.06, which are incredibly common for hunting.
To bring down a big animal like a deer, you use a big round and aim at the center of mass.

A two scalar triplets model as common origin for dark matter, neutrino masses, baryon asymmetry and inflation
Sin Kyu Kang, Raymundo Ramos
https://arxiv.org/abs/2510.07107 https…

A two scalar triplets model as common origin for dark matter, neutrino masses, baryon asymmetry and inflation
We propose an extension of the standard model (SM) by two SU(2) triplet scalars and an inert SU(2) doublet. We demonstrate that this setup can simultaneously produce an inflaton and baryon asymmetry in the early universe, provide a dark matter candidate and explain the smallness of neutrino masses. The two triplets are particularly important as they become mediators for the production of dark matter and the generation of lepton asymmetry, as well as contribute an inflaton. The inert doublet res…

Canine Clinical Gait Analysis for Orthopedic and Neurological Disorders: An Inertial Deep-Learning Approach
Netta Palez, L\'eonie Stra{\ss}, Sebastian Meller, Holger Volk, Anna Zamansky, Itzik Klein
https://arxiv.org/abs/2507.05671

Canine Clinical Gait Analysis for Orthopedic and Neurological Disorders: An Inertial Deep-Learning Approach
Canine gait analysis using wearable inertial sensors is gaining attention in veterinary clinical settings, as it provides valuable insights into a range of mobility impairments. Neurological and orthopedic conditions cannot always be easily distinguished even by experienced clinicians. The current study explored and developed a deep learning approach using inertial sensor readings to assess whether neurological and orthopedic gait could facilitate gait analysis. Our investigation focused on opt…

Spectral test of reducibility for Matrix tuples
Michael Stessin, Rongwei Yang
https://arxiv.org/abs/2509.05836 https://arxiv.org/pdf/2509.05836

Spectral test of reducibility for Matrix tuples
If a tuple of matrices has a common invariant subspace, its projective joint spectrum has an algebraic component. In general, the converse is not true, and there might be algebraic components in the projective joint spectrum without corresponding common invariant subspaces. In this paper we give necessary and sufficient conditions for the occurrence of such correspondence.

PDRs4All XIX. The 6 to 9 $\mu$m region as a probe of PAH charge and size in the Orion Bar
Baria Khan, Samuel A. Daza Rodriguez, Els Peeters, Alexander G. G. M. Tielens, Takashi Onaka, Jan Cami, Bethany Schefter, Christiaan Boersma, Felipe Alarc\'on, Olivier Bern\'e, Am\'elie Canin, Ryan Chown, Emmanuel Dartois, Javier R. Goicoechea, Emilie Habart, Olga Kannavou, Alexandros Maragkoudakis, Amit Pathak, Alessandra Ricca, Ga\"el Rouill\'e, Dinalva A. Sales, Ilane Schro…

PDRs4All XIX. The 6 to 9 $μ$m region as a probe of PAH charge and size in the Orion Bar
Infrared emission from polycyclic aromatic hydrocarbons (PAHs) play a major role in determining the charge balance of their host environments that include photo-dissociation regions (PDRs) in galaxies, planetary nebulae, and rims of molecular clouds. We aim to investigate the distribution and sizes of charged PAHs across the key zones of the Orion Bar PDR. We employ JWST MIRI-MRS observations of the Orion Bar from the Early Release Science program ''PDRs4All'' and synthetic images in the JWST M…

A complete system of inequalities for the diameter, in-, and circumradius in the 3-dimensional Euclidean space
Ren\'e Brandenberg, Bernardo Gonz\'alez Merino, Mia Runge
https://arxiv.org/abs/2509.05028

A complete system of inequalities for the diameter, in-, and circumradius in the 3-dimensional Euclidean space
We present a complete system of inequalities for the inradius, circumradius, and diameter in the $3$-dimensional Euclidean space. To do so, we prove quasiconcavity of the inradius evaluated over $n$-simplices with a common facet independently of the norm/gauge under consideration.

Learning Linear Regression with Low-Rank Tasks in-Context
Kaito Takanami, Takashi Takahashi, Yoshiyuki Kabashima
https://arxiv.org/abs/2510.04548 https://a…

Learning Linear Regression with Low-Rank Tasks in-Context
In-context learning (ICL) is a key building block of modern large language models, yet its theoretical mechanisms remain poorly understood. It is particularly mysterious how ICL operates in real-world applications where tasks have a common structure. In this work, we address this problem by analyzing a linear attention model trained on low-rank regression tasks. Within this setting, we precisely characterize the distribution of predictions and the generalization error in the high-dimensional li…