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The Power Spherical distribution

The Power Spherical distribution

8 June 2020
Nicola De Cao
Wilker Aziz
ArXivPDFHTML

Papers citing "The Power Spherical distribution"

20 / 20 papers shown
Title
vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter
vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter
Yitian Shi
Edgar Welte
Maximilian Gilles
Rania Rayyes
61
3
0
06 Nov 2024
Neural Ordinary Differential Equations on Manifolds
Neural Ordinary Differential Equations on Manifolds
Luca Falorsi
Patrick Forré
BDL
AI4CE
22
33
0
11 Jun 2020
Flows for simultaneous manifold learning and density estimation
Flows for simultaneous manifold learning and density estimation
Johann Brehmer
Kyle Cranmer
DRL
AI4CE
63
157
0
31 Mar 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
142
10,591
0
17 Feb 2020
Stochastic Normalizing Flows
Stochastic Normalizing Flows
Hao Wu
Jonas Köhler
Frank Noé
96
181
0
16 Feb 2020
Normalizing Flows on Tori and Spheres
Normalizing Flows on Tori and Spheres
Danilo Jimenez Rezende
George Papamakarios
S. Racanière
M. S. Albergo
G. Kanwar
P. Shanahan
Kyle Cranmer
TPM
42
153
0
06 Feb 2020
Increasing Expressivity of a Hyperspherical VAE
Increasing Expressivity of a Hyperspherical VAE
Tim R. Davidson
Jakub M. Tomczak
E. Gavves
25
6
0
07 Oct 2019
Block Neural Autoregressive Flow
Block Neural Autoregressive Flow
Nicola De Cao
Ivan Titov
Wilker Aziz
DRL
16
121
0
09 Apr 2019
A RAD approach to deep mixture models
A RAD approach to deep mixture models
Laurent Dinh
Jascha Narain Sohl-Dickstein
Hugo Larochelle
Razvan Pascanu
44
46
0
18 Mar 2019
Continuous Hierarchical Representations with Poincaré Variational
  Auto-Encoders
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
Emile Mathieu
Charline Le Lan
Chris J. Maddison
Ryota Tomioka
Yee Whye Teh
BDL
DRL
45
175
0
17 Jan 2019
Von Mises-Fisher Loss for Training Sequence to Sequence Models with
  Continuous Outputs
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
Sachin Kumar
Yulia Tsvetkov
31
70
0
10 Dec 2018
Explorations in Homeomorphic Variational Auto-Encoding
Explorations in Homeomorphic Variational Auto-Encoding
Luca Falorsi
P. D. Haan
Tim R. Davidson
Nicola De Cao
Maurice Weiler
Patrick Forré
Taco S. Cohen
BDL
DRL
74
117
0
12 Jul 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
199
5,024
0
19 Jun 2018
Implicit Reparameterization Gradients
Implicit Reparameterization Gradients
Michael Figurnov
S. Mohamed
A. Mnih
BDL
82
231
0
22 May 2018
Hyperspherical Variational Auto-Encoders
Hyperspherical Variational Auto-Encoders
Tim R. Davidson
Luca Falorsi
Nicola De Cao
Thomas Kipf
Jakub M. Tomczak
DRL
BDL
79
381
0
03 Apr 2018
SphereFace: Deep Hypersphere Embedding for Face Recognition
SphereFace: Deep Hypersphere Embedding for Face Recognition
Weiyang Liu
Yandong Wen
Zhiding Yu
Ming Li
Bhiksha Raj
Le Song
CVBM
198
2,790
0
26 Apr 2017
Reparameterization Gradients through Acceptance-Rejection Sampling
  Algorithms
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
C. A. Naesseth
Francisco J. R. Ruiz
Scott W. Linderman
David M. Blei
BDL
101
109
0
18 Oct 2016
Directional Statistics in Machine Learning: a Brief Review
Directional Statistics in Machine Learning: a Brief Review
S. Sra
HAI
25
43
0
01 May 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRL
BDL
238
4,143
0
21 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
622
149,474
0
22 Dec 2014
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