Weight

الوزن البنيوي

المعامل الحسابي الذي يحدد مدى قوة وتأثير الإشارة المارة عبر الرابط بين عصبونين.

Weight

Also translated asمعامل التأثير الرقمي، الثقل الحسابي للرابط

First appears in this corpus in: Nouvelles méthodes pour la détermination des orbites des comètes (Method of Least Squares) (1805)

Appears in these papers

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting1997 in the sky ✦
Intriguing Properties of Neural Networks2014 in the sky ✦
Mastering the Game of Go with Deep Neural Networks and Tree Search2016 in the sky ✦
Learning Representations by Back-Propagating Errors1986 in the sky ✦
Learning Long-Term Dependencies with Gradient Descent is Difficult1994 in the sky ✦
Neural Networks and the Bias/Variance Dilemma1992 in the sky ✦
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model2022 in the sky ✦
A Learning Algorithm for Boltzmann Machines1985 in the sky ✦
Unsupervised Visual Representation Learning by Context Prediction2015 in the sky ✦
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data2001 in the sky ✦
Cyclical Learning Rates for Training Neural Networks2017 in the sky ✦
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks2015 in the sky ✦
Continuous Control with Deep Reinforcement Learning2015 in the sky ✦
Reducing the Dimensionality of Data with Neural Networks2006 in the sky ✦
A Fast Learning Algorithm for Deep Belief Nets2006 in the sky ✦
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding2016 in the sky ✦
Deep Learning2015 in the sky ✦
DeepSeek-V3 Technical Report2024 in the sky ✦
Deformable Convolutional Networks2017 in the sky ✦
Extracting and Composing Robust Features with Denoising Autoencoders2008 in the sky ✦
Deep Interest Network for Click-Through Rate Prediction2018 in the sky ✦
Learning Distributed Representations of Concepts1986 in the sky ✦
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World2017 in the sky ✦
Human-Level Control Through Deep Reinforcement Learning2015 in the sky ✦
Dropout: A Simple Way to Prevent Neural Networks from Overfitting2014 in the sky ✦
Fast R-CNN2015 in the sky ✦
Explaining and Harnessing Adversarial Examples2015 in the sky ✦
Graph Attention Networks2018 in the sky ✦
A Generalist Agent2022 in the sky ✦
Gaussian Processes for Machine Learning2006 in the sky ✦
Semi-Supervised Classification with Graph Convolutional Networks2017 in the sky ✦
Gemma: Open Models Based on Gemini Research and Technology2024 in the sky ✦
Google's Neural Machine Translation System: Bridging the Gap Between Human and Machine Translation2016 in the sky ✦
The Graph Neural Network Model2009 in the sky ✦
Language Models Are Few-Shot Learners2020 in the sky ✦
GPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers2022 in the sky ✦
GPTQ: Accurate Post-Training Quantization for Generative Pre-Trained Transformers2022 in the sky ✦
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization2017 in the sky ✦
On the Difficulty of Training Recurrent Neural Networks2013 in the sky ✦
Inductive Representation Learning on Large Graphs2017 in the sky ✦
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling2014 in the sky ✦
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification2015 in the sky ✦
The Organization of Behavior: A Neuropsychological Theory1949 in the sky ✦
The Organization of Behavior: A Neuropsychological Theory1949 in the sky ✦
Highway Networks2015 in the sky ✦
Neural Networks and Physical Systems with Emergent Collective Computational Abilities1982 in the sky ✦
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset2017 in the sky ✦
Distilling the Knowledge in a Neural Network2015 in the sky ✦
Regression Shrinkage and Selection via the Lasso1996 in the sky ✦
Nouvelles méthodes pour la détermination des orbites des comètes (Method of Least Squares)1805 in the sky ✦
Visualizing the Loss Landscape of Neural Nets2018 in the sky ✦
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks2019 in the sky ✦
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks2019 in the sky ✦
A Logical Calculus of the Ideas Immanent in Nervous Activity1943 in the sky ✦
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism2019 in the sky ✦
Mixed Precision Training2018 in the sky ✦
Natural Gradient Works Efficiently in Learning1998 in the sky ✦
Neocognitron: A Self-Organizing Neural Network Model for Pattern Recognition1980 in the sky ✦
A Neural Probabilistic Language Model2003 in the sky ✦
Neural Tangent Kernel: Convergence and Generalization in Neural Networks2018 in the sky ✦
Neural Tangent Kernel: Convergence and Generalization in Neural Networks2018 in the sky ✦
Optimal Brain Damage1989 in the sky ✦
The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain1958 in the sky ✦
Perceptrons: An Introduction to Computational Geometry1969 in the sky ✦
Random Features for Large-Scale Kernel Machines2007 in the sky ✦
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning1992 in the sky ✦
Rectified Linear Units Improve Restricted Boltzmann Machines2010 in the sky ✦
RMSProp: Divide the Gradient by a Running Average of Its Recent Magnitude2012 in the sky ✦
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control2023 in the sky ✦
Some Studies in Machine Learning Using the Game of Checkers1959 in the sky ✦
Scaling Laws for Neural Language Models2020 in the sky ✦
Sequence to Sequence Learning with Neural Networks2014 in the sky ✦
SGDR: Stochastic Gradient Descent with Warm Restarts2017 in the sky ✦
Signature Verification Using a "Siamese" Time Delay Neural Network1993 in the sky ✦
Temporal Difference Learning and TD-Gammon1995 in the sky ✦
Approximation by Superpositions of a Sigmoidal Function1989 in the sky ✦
Approximation by Superpositions of a Sigmoidal Function1989 in the sky ✦
Distributed Representations of Words and Phrases and Their Compositionality2013 in the sky ✦
Understanding the Difficulty of Training Deep Feedforward Neural Networks2010 in the sky ✦
Understanding the Difficulty of Training Deep Feedforward Neural Networks2010 in the sky ✦