English
Related papers

Related papers: Information Theory and Direction Selectivity

200 papers

Changes in a cell's external or internal conditions are usually reflected in the concentrations of the relevant transcription factors. These proteins in turn modulate the expression levels of the genes under their control and sometimes need…

Molecular Networks · Quantitative Biology 2013-08-01 Gasper Tkacik , Curtis G Callan , William Bialek

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

Numerical analysts might be expected to pay close attention to a branch of complexity theory called information-based complexity theory (IBCT), which produces an abundance of impressive results about the quest for approximate solutions to…

Numerical Analysis · Mathematics 2025-10-20 Beresford N. Parlett

We present results of a self-consistent model of the spectral energy distribution (SED) of starburst galaxies. Two parameters control the IR SED, the mean pressure in the ISM and the destruction timescale of molecular clouds. Adding a…

Astrophysics · Physics 2009-11-10 M. A. Dopita

The development of single-cell technologies provides the opportunity to identify new cellular states and reconstruct novel cell-to-cell relationships. Applications range from understanding the transcriptional and epigenetic processes…

Quantitative Methods · Quantitative Biology 2018-10-11 Luis Aparicio , Mykola Bordyuh , Andrew J. Blumberg , Raul Rabadan

Information theory gives rise to a novel method for causal skeleton discovery by expressing associations between variables as tensors. This tensor-based approach reduces the dimensionality of the data needed to test for conditional…

Machine Learning · Statistics 2020-11-10 David Sigtermans

State-of-the-art text-to-image models excel at photorealistic rendering but often struggle to capture the layout and object relationships implied by complex prompts. Scene graphs provide a natural structural prior, yet previous graph-guided…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Thanh-Nhan Vo , Trong-Thuan Nguyen , Tam V. Nguyen , Minh-Triet Tran

Diffusion models transform noise into data by injecting information that was captured in their neural network during the training phase. In this paper, we ask: \textit{what} is this information? We find that, in pixel-space diffusion…

Machine Learning · Computer Science 2026-02-02 Akhil Premkumar

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Simon R. Schultz , Stefano Panzeri

Information theory is a statistical theory concerned with the relative state of detectors and physical systems. As a consequence, the classical framework of Shannon needs to be extended to deal with quantum detectors, possibly moving at…

Quantum Physics · Physics 2007-05-23 Christoph Adami

In this work, we study two models of arbitrarily varying channels, when causal side information is available at the encoder in a causal manner. First, we study the arbitrarily varying channel (AVC) with input and state constraints, when the…

Information Theory · Computer Science 2017-01-23 Uzi Pereg , Yossef Steinberg

A mathematical framework for information-theoretic analysis is established, with a new viewpoint of describing transmitted messages and communication channels by the nonlinear expectation theory, beyond the framework of classical…

Information Theory · Computer Science 2026-03-18 Wen-Xuan Lang , Shaoshi Yang , Jianhua Zhang , Zhiming Ma

We propose an effect called information constraint which is characterized by the existence of different decay rates of signal strengths propagating along opposite directions. It is an intrinsic property of a type of open quantum system,…

Mesoscale and Nanoscale Physics · Physics 2021-11-18 Chun-Hui Liu , Shu Chen

This paper provides an elementary, self-contained analysis of diffusion-based sampling methods for generative modeling. In contrast to existing approaches that rely on continuous-time processes and then discretize, our treatment works…

Machine Learning · Statistics 2025-06-25 Galen Reeves , Henry D. Pfister

With the advent of space-based precision photometry missions the quantity and quality of starspot light curves has greatly increased. This paper presents a large number of starspot models and their resulting light curves to: 1) better…

Solar and Stellar Astrophysics · Physics 2020-08-13 Gibor Basri , Riya Shah

A stochastic nonlinear dynamical system generates information, as measured by its entropy rate. Some---the ephemeral information---is dissipated and some---the bound information---is actively stored and so affects future behavior. We derive…

Statistical Mechanics · Physics 2015-06-19 Sarah Marzen , James P. Crutchfield

Contemporary sequential recommendation methods are becoming more complex, shifting from classification to a diffusion-guided generative paradigm. However, the quality of guidance in the form of user information is often compromised by…

Information Retrieval · Computer Science 2026-02-16 Qilong Yan , Yifei Xing , Dugang Liu , Jingpu Duan , Jian Yin

CONTEXT: Spectral-line asymmetries and wavelength shifts are signatures of hydrodynamics in solar and stellar atmospheres. Theory may precisely predict idealized lines, but observed spectra are limited by blends, too few suitable lines,…

Astrophysics · Physics 2009-11-13 Dainis Dravins

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Simon R. Schultz , Robin A. A. Ince , Stefano Panzeri

Generative AI models have recently achieved astonishing results in quality and are consequently employed in a fast-growing number of applications. However, since they are highly data-driven, relying on billion-sized datasets randomly…