M. Fraccaro

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All published works

Action	Title	Year	Authors
+	BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling	2019	Lars Maaløe M. Fraccaro Valentin Liévin Ole Winther
+	An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models.	2018	Ulrich Paquet M. Fraccaro
+	Generative Temporal Models with Spatial Memory for Partially Observed Environments	2018	M. Fraccaro Danilo Jimenez Rezende Yori Zwólš Alexander Pritzel S. M. Ali Eslami Fabio Viola
+	Generative Temporal Models with Spatial Memory for Partially Observed Environments	2018	M. Fraccaro Danilo Jimenez Rezende Yori Zwólš Alexander Pritzel S. M. Ali Eslami Fabio Viola
+	An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models	2018	Ulrich Paquet M. Fraccaro
+	Semi-Supervised Generation with Cluster-aware Generative Models	2017	Lars Maaløe M. Fraccaro Ole Winther
+	A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning	2017	M. Fraccaro Simon Kamronn Ulrich Paquet Ole Winther
+	An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants	2016	M. Fraccaro Ulrich Paquet Ole Winther
+	Sequential Neural Models with Stochastic Layers	2016	M. Fraccaro Søren Kaae Sønderby Ulrich Paquet Ole Winther

Common Coauthors

Coauthor	Papers Together
Ole Winther	5
Ulrich Paquet	5
Fabio Viola	2
S. M. Ali Eslami	2
Danilo Jimenez Rezende	2
Alexander Pritzel	2
Lars Maaløe	2
Yori Zwólš	2
Valentin Liévin	1
Simon Kamronn	1
Søren Kaae Sønderby	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Stochastic Backpropagation and Approximate Inference in Deep Generative Models	2014	Danilo Jimenez Rezende Shakir Mohamed Daan Wierstra	3
+	Semi-Supervised Learning with Deep Generative Models	2014	Diederik P. Kingma Danilo Jimenez Rezende Shakir Mohamed Max Welling	2
+	Distributional Smoothing with Virtual Adversarial Training	2016	Takeru Miyato Shin‐ichi Maeda Masanori Koyama Ken Nakae Shin Ishii	2
+	Categorical Reparameterization with Gumbel-Softmax	2016	Eric Jang Shixiang Gu Ben Poole	2
+	The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables	2016	Chris J. Maddison Andriy Mnih Yee Whye Teh	2
+	Importance Weighted Autoencoders	2015	Yuri Burda Roger Grosse Ruslan Salakhutdinov	2
+	Improved Techniques for Training GANs	2016	Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen	2
+	Discrete Variational Autoencoders	2017	Jason Tyler Rolfe	2
+	Semi-Supervised Learning with Ladder Networks	2015	Antti Rasmus Harri Valpola Mikko Honkala Mathias Berglund Tapani Raiko	2
+	Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks	2015	Jost Tobias Springenberg	2
+ PDF Chat	Monte Carlo Statistical Methods	2000	Hoon Kim Christian P. Robert George Casella	1
+ PDF Chat	Simulating normalizing constants: from importance sampling to bridge sampling to path sampling	1998	Andrew Gelman Xiao‐Li Meng	1
+	Sequential Monte Carlo	1962	John H. Halton	1
+	Sequential Monte Carlo Methods for Dynamic Systems	1998	Jun S. Liu Rong Chen	1
+ PDF Chat	Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference	2004	Nicolás Chopin	1
+	Perturbative corrections for approximate inference in Gaussian latent variable models	2013	Manfred Opper Ulrich Paquet Ole Winther	1
+	Action-Conditional Video Prediction using Deep Networks in Atari Games	2015	Junhyuk Oh Xiaoxiao Guo Honglak Lee Richard L. Lewis Satinder Singh	1
+	Variational Bayesian Inference with Stochastic Search	2012	David M. Blei Michael I. Jordan John Paisley	1
+	Annealing between distributions by averaging moments	2013	Roger Grosse Chris J. Maddison Ruslan Salakhutdinov	1
+	How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?	2015	Allan De Freitas François Septier Lyudmila Mihaylova Simon Godsill	1
+	Sequential Monte Carlo for Graphical Models	2014	Christian A. Naesseth Fredrik Lindsten Thomas B. Schön	1
+	Asynchronous Anytime Sequential Monte Carlo	2014	Brooks Paige Frank Wood Arnaud Doucet Yee Whye Teh	1
+ PDF Chat	Sequential Monte Carlo Samplers	2006	Pierre Del Moral Arnaud Doucet Ajay Jasra	1
+ PDF Chat	Representation Learning: A Review and New Perspectives	2013	Yoshua Bengio Aaron Courville P. M. Durai Raj Vincent	1
+	Stochastic variational inference	2013	Matthew D. Hoffman David M. Blei Chong Wang John Paisley	1
+ PDF Chat	Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments	2014	Christopher Nemeth Paul Fearnhead Lyudmila Mihaylova	1
+	Spatio-temporal video autoencoder with differentiable memory	2015	Viorica Pătrăucean Ankur Handa Roberto Cipolla	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Generating Sentences from a Continuous Space	2015	Samuel R. Bowman Luke Vilnis Oriol Vinyals Andrew M. Dai Rafał Józefowicz Samy Bengio	1
+	Black box variational inference for state space models	2015	Evan Archer Il Memming Park Lars Buesing John P. Cunningham Liam Paninski	1
+	Auxiliary Deep Generative Models	2016	Lars Maaløe Casper Kaae Sønderby Søren Kaae Sønderby Ole Winther	1
+	An Adaptive Resample-Move Algorithm for Estimating Normalizing Constants	2016	M. Fraccaro Ulrich Paquet Ole Winther	1
+	Backprop KF: Learning Discriminative Deterministic State Estimators	2016	Tuomas Haarnoja Anurag Ajay Sergey Levine Pieter Abbeel	1
+	Sequential Neural Models with Stochastic Layers	2016	M. Fraccaro Søren Kaae Sønderby Ulrich Paquet Ole Winther	1
+	Density estimation using Real NVP	2016	Laurent Dinh Jascha Sohl‐Dickstein Samy Bengio	1
+	Conditional Image Generation with PixelCNN Decoders	2016	Aäron van den Oord Nal Kalchbrenner Oriol Vinyals Lasse Espeholt Alex Graves Koray Kavukcuoglu	1
+	Composing graphical models with neural networks for structured representations and fast inference	2016	Matthew Johnson David Duvenaud Alexander B. Wiltschko Sandeep Robert Datta Ryan P. Adams	1
+ PDF Chat	Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network	2016	Wenzhe Shi José Caballero Ferenc Huszár Johannes Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang	1
+	Hot coupling: a particle approach to inference and normalization on pairwise undirected graphs of arbitrary topology	2005	Firas Hamze Nando de Freitas	1
+	Structured Inference Networks for Nonlinear State Space Models	2016	Rahul G. Krishnan Uri Shalit David Sontag	1
+	Improving Variational Auto-Encoders using Householder Flow	2016	Jakub M. Tomczak Max Welling	1
+	Towards Deeper Understanding of Variational Autoencoding Models	2017	Shengjia Zhao Jiaming Song Stefano Ermon	1
+	Triple Generative Adversarial Nets	2017	Chongxuan Li Kun Xu Jun Zhu Bo Zhang	1
+	Recurrent Environment Simulators	2017	Silvia Chiappa Sébastien Racanière Daan Wierstra Shakir Mohamed	1
+	Semi-Supervised Generation with Cluster-aware Generative Models	2017	Lars Maaløe M. Fraccaro Ole Winther	1
+ PDF Chat	Generating Sentences Using a Dynamic Canvas	2018	Harshil Shah Bowen Zheng David Barber	1
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	1
+	WaveNet: A Generative Model for Raw Audio	2016	Aäron van den Oord Sander Dieleman Heiga Zen Karen Simonyan Oriol Vinyals Alex Graves Nal Kalchbrenner Andrew Senior Koray Kavukcuoglu	1
+	PixelVAE: A Latent Variable Model for Natural Images	2016	Ishaan Gulrajani Kundan Kumar Faruk Ahmed Adrien Ali Taïga Francesco Visin David Vázquez Aaron Courville	1
+	A Recurrent Latent Variable Model for Sequential Data	2015	Jun‐Young Chung Kyle Kastner Laurent Dinh Kratarth Goel Aaron Courville Yoshua Bengio	1