Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
文献紹介 / Knowledge Tracing with GNN
Search
Atom
December 04, 2020
0
82
文献紹介 / Knowledge Tracing with GNN
文献紹介と書いてあるが自分の用のメモ
公開しなくても良いかなと思ったが公開
Atom
December 04, 2020
Tweet
Share
More Decks by Atom
See All by Atom
文献紹介 / Structure-based Knowledge Tracing: An Influence Propagation View
roraidolaurent
0
80
文献紹介 / Non-Intrusive Parametric Reduced Order Models withHigh-Dimensional Inputs via Gradient-Free Active Subspace
roraidolaurent
0
50
ニューラルネットワークのベイズ推論 / Bayesian inference of neural networks
roraidolaurent
1
2.8k
Graph Convolutional Networks
roraidolaurent
0
220
文献紹介 / A Probabilistic Annotation Model for Crowdsourcing Coreference
roraidolaurent
0
62
文献紹介Deep Temporal-Recurrent-Replicated-Softmax for Topical Trends over Time
roraidolaurent
0
93
文献紹介/ Bayesian Learning for Neural Dependency Parsing
roraidolaurent
0
100
ポッキー数列の加法定理 / Pocky number additon theorem
roraidolaurent
0
200
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling
roraidolaurent
1
130
Featured
See All Featured
The Art of Programming - Codeland 2020
erikaheidi
53
13k
Build The Right Thing And Hit Your Dates
maggiecrowley
34
2.6k
The Cult of Friendly URLs
andyhume
78
6.3k
Product Roadmaps are Hard
iamctodd
PRO
52
11k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
PRO
17
1.1k
Building Applications with DynamoDB
mza
94
6.3k
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
12
620
Understanding Cognitive Biases in Performance Measurement
bluesmoon
28
1.6k
Optimising Largest Contentful Paint
csswizardry
35
3.2k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
367
25k
Fontdeck: Realign not Redesign
paulrobertlloyd
83
5.5k
How To Stay Up To Date on Web Technology
chriscoyier
790
250k
Transcript
None
None
∈ , ∈ {0,1}2 ∈ {0,1} ∈ {0,1} + 1
≡ +1 = , , , = 1 , ⋯ , ⊆ × , ∈ ℝ× ∈ ∈ ℝ
None
∈ ℝ2× ∈ ℝ× () ∈ ℝ ∈
, ℎ
None
None
None
None
None
None
☓
None
None
∈ {0,1}
None
None
None
−1 から問題 (スキル をもつ)に正答確率を アテンションで求めるが, と同じスキルをもつ問題(例 )
の正誤情報 は −1 では失われている可能性が大きい. に関連する問題を選択し, その情報 についても アテンションをとる.
None
None
None
None
None
None
None