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Bidirectional Recurrent Neural Networks as Generative Models -
  Reconstructing Gaps in Time Series

Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series

7 April 2015
Mathias Berglund
T. Raiko
Mikko Honkala
L. Kärkkäinen
A. Vetek
J. Karhunen
    BDL
ArXivPDFHTML

Papers citing "Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series"

15 / 15 papers shown
Title
Machine Generated Text: A Comprehensive Survey of Threat Models and
  Detection Methods
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Evan Crothers
Nathalie Japkowicz
H. Viktor
DeLMO
38
107
0
13 Oct 2022
A Latent Feature Analysis-based Approach for Spatio-Temporal Traffic
  Data Recovery
A Latent Feature Analysis-based Approach for Spatio-Temporal Traffic Data Recovery
Yuting Ding
Dingjie Wu
16
0
0
16 Aug 2022
projUNN: efficient method for training deep networks with unitary
  matrices
projUNN: efficient method for training deep networks with unitary matrices
B. Kiani
Randall Balestriero
Yann LeCun
S. Lloyd
43
32
0
10 Mar 2022
Parallel Refinements for Lexically Constrained Text Generation with BART
Parallel Refinements for Lexically Constrained Text Generation with BART
Xingwei He
29
39
0
26 Sep 2021
Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic
  Data Imputation with Complex Missing Patterns
Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns
Yuebing Liang
Zhan Zhao
Lijun Sun
GNN
AI4TS
35
61
0
17 Sep 2021
Sequence Generation using Deep Recurrent Networks and Embeddings: A
  study case in music
Sequence Generation using Deep Recurrent Networks and Embeddings: A study case in music
Sebastian Garcia-Valencia
Alejandro Betancourt
Juan Guillermo Lalinde Pulido
MGen
25
6
0
02 Dec 2020
Language Generation via Combinatorial Constraint Satisfaction: A Tree
  Search Enhanced Monte-Carlo Approach
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach
Maosen Zhang
Nan Jiang
Lei Li
Yexiang Xue
27
4
0
24 Nov 2020
Convolutional Autoencoders for Human Motion Infilling
Convolutional Autoencoders for Human Motion Infilling
Manuel Kaufmann
Emre Aksan
Mingli Song
Fabrizio Pece
R. Ziegler
Otmar Hilliges
3DH
15
97
0
22 Oct 2020
A Generalized Framework of Sequence Generation with Application to
  Undirected Sequence Models
A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models
Elman Mansimov
Alex Jinpeng Wang
Sean Welleck
Kyunghyun Cho
AIMat
25
46
0
29 May 2019
Discrete Flows: Invertible Generative Models of Discrete Data
Discrete Flows: Invertible Generative Models of Discrete Data
Dustin Tran
Keyon Vafa
Kumar Krishna Agrawal
Laurent Dinh
Ben Poole
DRL
24
114
0
24 May 2019
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling
Ning Miao
Hao Zhou
Lili Mou
Rui Yan
Lei Li
31
191
0
14 Nov 2018
Deep Segment Hash Learning for Music Generation
Deep Segment Hash Learning for Music Generation
Kevin Joslyn
Naifan Zhuang
K. Hua
8
6
0
30 May 2018
BRITS: Bidirectional Recurrent Imputation for Time Series
BRITS: Bidirectional Recurrent Imputation for Time Series
Wei Cao
Dong Wang
Jian Li
Hao Zhou
Lei Li
Yitan Li
AI4TS
28
604
0
27 May 2018
Bidirectional Beam Search: Forward-Backward Inference in Neural Sequence
  Models for Fill-in-the-Blank Image Captioning
Bidirectional Beam Search: Forward-Backward Inference in Neural Sequence Models for Fill-in-the-Blank Image Captioning
Q. Sun
Stefan Lee
Dhruv Batra
BDL
30
43
0
24 May 2017
Tunable Efficient Unitary Neural Networks (EUNN) and their application
  to RNNs
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing
Yichen Shen
T. Dubček
J. Peurifoy
S. Skirlo
Yann LeCun
Max Tegmark
Marin Soljacic
17
176
0
15 Dec 2016
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