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Methods/CRN

CRN

Conditional Relation Network

Computer VisionIntroduced 200044 papers
Source Paper

Description

Conditional Relation Network, or CRN, is a building block to construct more sophisticated structures for representation and reasoning over video. CRN takes as input an array of tensorial objects and a conditioning feature, and computes an array of encoded output objects. Model building becomes a simple exercise of replication, rearrangement and stacking of these reusable units for diverse modalities and contextual information. This design thus supports high-order relational and multi-step reasoning.

Papers Using This Method

Energy Transduction in Complex Networks with Multiple Resources: The Chemistry Paradigm2025-05-02Stability in Reaction Network Models via an Extension of the Next Generation Matrix Method2024-11-03Noise-robust chemical reaction networks training artificial neural networks2024-10-15Neural CRNs: A Natural Implementation of Learning in Chemical Reaction Networks2024-08-18Understanding Multistationarity of Fully Open Reaction Networks2024-07-01Gears in Chemical Reaction Networks: Optimizing Energy Transduction Efficiency2024-05-28Antigenic Cooperation in Viral Populations: Redistribution of Loads Among Altruistic Viruses and Maximal Load per Altruist2024-05-28SICRN: Advancing Speech Enhancement through State Space Model and Inplace Convolution Techniques2024-02-22Computing Threshold Circuits with Void Reactions in Step Chemical Reaction Networks2024-02-13Cramer-Rao bound and absolute sensitivity in chemical reaction networks2024-01-13A Refining Underlying Information Framework for Monaural Speech Enhancement2023-12-18On a model of online analog computation in the cell with absolute functional robustness: algebraic characterization, function compiler and error control2023-10-23Thermodynamics of Growth in Open Chemical Reaction Networks2023-10-12Magnitude-and-phase-aware Speech Enhancement with Parallel Sequence Modeling2023-10-11Information geometric bound on general chemical reaction networks2023-09-19Efficient Acoustic Echo Suppression with Condition-Aware Training2023-07-28Timely Target Tracking: Distributed Updating in Cognitive Radar Networks2023-07-24Division Gets Better: Learning Brightness-Aware and Detail-Sensitive Representations for Low-Light Image Enhancement2023-07-18On Estimating Derivatives of Input Signals in Biochemistry2023-07-10Universal Slow Dynamics of Chemical Reaction Networks2023-04-20