filmov
tv
Kaiming Initialization (Q&A) | Lecture 5 (Part 1) | Applied Deep Learning (Supplementary)
Показать описание
Delving Deep into Rectifiers:Surpassing Human-Level Performance on ImageNet Classification
Maziar Raissi
Рекомендации по теме
1:10:36
18-backpropagation examples, weight initialization
1:07:19
Discussion 12 Training Neural Networks Part I - Activations, Preprocessing, Weight Initialization
0:27:26
Tutorial 4: Optimization and Initialization (Part 1)
0:09:44
NN - 18 - Weight Initialization 1 - What not to do?
0:57:57
Weights initialization & Associative Memory Part I
1:26:56
Lecture 6 - Fully connected networks, optimization, initialization
0:16:17
XAVIER & KAIMING WEIGHT INITIALISATION | DROPOUT & L2 REGULARIZATION | MALAYALAM | #AIL411 L...
0:45:28
Pierre Wolinski: Gaussian Pre-Activations in Neural Networks: Myth or Reality?
0:12:44
What's Hidden in a Randomly Weighted Neural Network?
0:35:34
Human-Computer QA: Dynamic Memory Networks for Visual and Textual Question Answering
0:29:34
10. Training neural networks, Part I - 10.2 Data preprocessing, weight initialization
1:56:33
Lesson 17: Deep Learning Foundations to Stable Diffusion
0:37:40
11785 Deep Learning Recitation 8: RNN Basics
0:17:53
Rethinking Pre-training and Self-Training
0:28:43
Self-Supervised Learning
0:42:16
Regularizing neural networks using constrained thermodynamic algorithms, Ben Leimkuhler
0:55:56
Webinar on, “Image Analysis using Deep Neural Networks
0:26:12
Math for Game Programmers: The Math of Deep Learning
0:23:42
On the Weight Dynamics of Deep Normalized Networks - ArXiv:2306.00700
1:00:49
D2 2020 AI4ESS Summer School David Hall
0:27:17
From Obstacle Problems to Neural Insights: Feed Forward Neural Network Modeling of Ice T
0:15:10
Momentum Predictive Representations Explained!
0:17:52
Stack More Layers Differently: High-Rank Training Through Low-Rank Updates
1:51:32
13L – Optimisation for Deep Learning