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Deep generative models seek to recover the process with which the observed data was generated. They may be used to synthesize new samples or to subsequently extract representations. Successful approaches in the domain of images are driven…

计算机视觉与模式识别 · 计算机科学 2020-07-27 Sjoerd van Steenkiste , Karol Kurach , Jürgen Schmidhuber , Sylvain Gelly

Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in structural properties, in turn, can affect the outcomes of…

社会与信息网络 · 计算机科学 2018-09-18 Peter Overbury , István Z. Kiss , Luc Berthouze

Multiple binomial sums form a large class of multi-indexed sequences, closed under partial summation, which contains most of the sequences obtained by multiple summation of products of binomial coefficients and also all the sequences with…

符号计算 · 计算机科学 2023-06-12 Alin Bostan , Pierre Lairez , Bruno Salvy

A curious phenomenon observed in some dynamical generative models is the following: despite learning errors in the score function or the drift vector field, the generated samples appear to shift \emph{along} the support of the data…

机器学习 · 计算机科学 2025-08-12 Nisha Chandramoorthy , Adriaan de Clercq

Ultrafinitism postulates that we can only compute on relatively short objects, and numbers beyond certain value are not available. This approach would also forbid many forms of infinitary reasoning and allow to remove certain paradoxes…

编程语言 · 计算机科学 2024-08-22 Michał J. Gajda

This paper introduces and outlines a new integrative field, Ideometrics. It is the systematic science of generating, evaluating, and prioritising ideas, based on the proposed sense of ideas and assigning value to information by the brain.…

物理与社会 · 物理学 2025-08-13 Igor Rudan , Aziz Sheikh

This paper contributes to the theory of large cardinals beyond the Kunen inconsistency, or choiceless large cardinal axioms, in the context where the Axiom of Choice is not assumed. The first part of the paper investigates a periodicity…

逻辑 · 数学 2021-02-19 Gabriel Goldberg

I formalize the ontology of apocalyptic events as synchronized morphogenetic manifolds within the framework of Thom's catastrophe theory. Local catastrophes (folds, cusps, umbilici) are extended to higher-order systemic collapses through…

动力系统 · 数学 2025-10-31 Rolando Manuel Gonzales Martinez

In the age of artificial intelligence and biotechnology, a unified understanding of technology and biology is critically needed but still lacking. A cornerstone of such unification is evolvable design. I present a formalism, called goal…

物理与社会 · 物理学 2025-07-15 Dániel Czégel

Continuous attractors are critical for information processing in both biological and artificial neural systems, with implications for spatial navigation, memory, and deep learning optimization. However, existing research lacks a unified…

机器学习 · 计算机科学 2025-09-16 Shaoxin Tian , Hongkai Liu , Yuying Yang , Jiali Yu , Zizheng Miao , Xuming Huang , Zhishuai Liu , Zhang Yi

"If it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous successive, slight modifications, my theory would absolutely break down". Can Darwinian random mutations and selection…

综合物理 · 物理学 2015-03-19 A. Sengupta

The architectural blueprint of today's leading text-to-image models contains a fundamental flaw: an inability to handle logical composition. This survey investigates this breakdown across three core primitives-negation, counting, and…

计算机视觉与模式识别 · 计算机科学 2025-11-14 Mayank Vatsa , Aparna Bharati , Richa Singh

Disentanglement is a useful property in representation learning which increases the interpretability of generative models such as Variational autoencoders (VAE), Generative Adversarial Models, and their many variants. Typically in such…

机器学习 · 计算机科学 2022-05-31 Arun Pandey , Michael Fanuel , Joachim Schreurs , Johan A. K. Suykens

Neural networks embed the geometric structure of a data manifold lying in a high-dimensional space into latent representations. Ideally, the distribution of the data points in the latent space should depend only on the task, the data, the…

Understanding how the brain encodes stimuli has been a fundamental problem in computational neuroscience. Insights into this problem have led to the design and development of artificial neural networks that learn representations by…

神经元与认知 · 定量生物学 2025-12-04 Shubham Choudhary , Paul Masset , Demba Ba

Most models of generative AI for images assume that images are inherently low-dimensional objects embedded within a high-dimensional space. Additionally, it is often implicitly assumed that thematic image datasets form smooth or piecewise…

计算机视觉与模式识别 · 计算机科学 2026-01-16 Leah Bar , Liron Mor Yosef , Shai Zucker , Neta Shoham , Inbar Seroussi , Nir Sochen

We present MMbeddings, a probabilistic embedding approach that reinterprets categorical embeddings through the lens of nonlinear mixed models, effectively bridging classical statistical theory with modern deep learning. By treating…

机器学习 · 统计学 2025-11-04 Giora Simchoni , Saharon Rosset

Pluridisciplinar convergence is a major problem that had emerged with Human-Artefact Systems and so-called " Augmented Humanity " as academical fields and even more as technical fields. Problems come mainly from the juxtaposition of two…

人机交互 · 计算机科学 2016-02-12 Rémi Nazin , Didier Fass

Potentialism is the view that objects are successively generated in an incompletable process. A strict version of the view adds that truths are successively determined. Strict potentialism can be analyzed using two modalities: one for the…

逻辑 · 数学 2026-04-21 Øystein Linnebo

A reconciliation of gravitation and electromagnetism has eluded physics for neearly a century. It is argued here that this is because both quantum physics and classical physics are set in differentiable space time manifolds with point…

综合物理 · 物理学 2007-05-23 B. G. Sidharth
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