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1808.03856
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Neural Importance Sampling
11 August 2018
Thomas Müller
Brian McWilliams
Fabrice Rousselle
Markus Gross
Jan Novák
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Papers citing
"Neural Importance Sampling"
50 / 185 papers shown
Title
On Embeddings for Numerical Features in Tabular Deep Learning
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Generative Modeling for Low Dimensional Speech Attributes with Neural Spline Flows
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Rafael Valle
Rohan Badlani
J. F. Santos
Bryan Catanzaro
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0
03 Mar 2022
Differentiable Neural Radiosity
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Matthias Zwicker
54
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0
31 Jan 2022
Tracking and Planning with Spatial World Models
Baris Kayalibay
Atanas Mirchev
Patrick van der Smagt
Justin Bayer
78
2
0
25 Jan 2022
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller
Alex Evans
Christoph Schied
A. Keller
391
4,071
0
16 Jan 2022
Global convergence of optimized adaptive importance samplers
Ömer Deniz Akyildiz
103
7
0
02 Jan 2022
Uniform-in-Phase-Space Data Selection with Iterative Normalizing Flows
M. Hassanaly
Bruce A. Perry
M. Mueller
S. Yellapantula
67
5
0
28 Dec 2021
Solving time dependent Fokker-Planck equations via temporal normalizing flow
Xiaodong Feng
Li Zeng
Tao Zhou
AI4CE
79
25
0
28 Dec 2021
Autoregressive Quantile Flows for Predictive Uncertainty Estimation
Phillip Si
Allan Bishop
Volodymyr Kuleshov
BDL
UQCV
AI4TS
199
20
0
09 Dec 2021
Path Guiding Using Spatio-Directional Mixture Models
Ana Dodik
Marios Papas
Cengiz Öztireli
Thomas Müller
72
18
0
25 Nov 2021
Generalized Normalizing Flows via Markov Chains
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDL
DiffM
AI4CE
94
25
0
24 Nov 2021
Bootstrap Your Flow
Laurence Illing Midgley
Vincent Stimper
G. Simm
José Miguel Hernández-Lobato
60
5
0
22 Nov 2021
Neural BRDFs: Representation and Operations
Jiahui Fan
Beibei Wang
Miloš Hašan
Jian Yang
Ling-Qi Yan
AI4CE
56
6
0
06 Nov 2021
Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems
Mansur Arief
Yuanlu Bai
Wenhao Ding
Shengyi He
Zhiyuan Huang
Henry Lam
Ding Zhao
39
14
0
03 Nov 2021
Sinusoidal Flow: A Fast Invertible Autoregressive Flow
Yumou Wei
TPM
28
0
0
26 Oct 2021
Generative Networks for Precision Enthusiasts
A. Butter
Theo Heimel
Sander Hummerich
Tobias Krebs
Tilman Plehn
Armand Rousselot
Sophia Vent
AI4CE
80
60
0
22 Oct 2021
Learning Stable Vector Fields on Lie Groups
Julen Urain
Davide Tateo
Jan Peters
84
18
0
22 Oct 2021
Smooth Normalizing Flows
Jonas Köhler
Andreas Krämer
Frank Noé
105
55
0
01 Oct 2021
Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint
Paul Hagemann
J. Hertrich
Gabriele Steidl
BDL
110
40
0
23 Sep 2021
Dynamic Diffuse Global Illumination Resampling
Z. Majercik
Thomas Müller
A. Keller
Derek Nowrouzezahrai
M. McGuire
46
15
0
11 Aug 2021
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods
Marylou Gabrié
Grant M. Rotskoff
Eric Vanden-Eijnden
50
21
0
16 Jul 2021
Sparse Flows: Pruning Continuous-depth Models
Lucas Liebenwein
Ramin Hasani
Alexander Amini
Daniela Rus
116
17
0
24 Jun 2021
Real-time Neural Radiance Caching for Path Tracing
Thomas Müller
Fabrice Rousselle
Jan Novák
A. Keller
3DH
AI4CE
121
167
0
23 Jun 2021
Nested Variational Inference
Heiko Zimmermann
Hao Wu
Babak Esmaeili
Jan-Willem van de Meent
BDL
83
21
0
21 Jun 2021
Improving the expressiveness of neural vocoding with non-affine Normalizing Flows
Adam Gabry's
Yunlong Jiao
V. Klimkov
Daniel Korzekwa
Roberto Barra-Chicote
43
1
0
16 Jun 2021
Densely connected normalizing flows
Matej Grcić
Ivan Grubišić
Sinisa Segvic
TPM
95
59
0
08 Jun 2021
Density estimation on smooth manifolds with normalizing flows
Dimitris Kalatzis
J. Z. Ye
Alison Pouplin
Jesper Wohlert
Søren Hauberg
86
6
0
07 Jun 2021
Neural Radiosity
Saeed Hadadan
Shuhong Chen
Matthias Zwicker
57
44
0
26 May 2021
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
Dian Wu
R. Rossi
Giuseppe Carleo
92
30
0
12 May 2021
Understanding Event-Generation Networks via Uncertainties
Marco Bellagente
Manuel Haussmann
Michel Luchmann
Tilman Plehn
BDL
118
55
0
09 Apr 2021
Appearance-Driven Automatic 3D Model Simplification
J. Hasselgren
Jacob Munkberg
J. Lehtinen
M. Aittala
S. Laine
90
56
0
08 Apr 2021
NeuMIP: Multi-Resolution Neural Materials
Alexandr Kuznetsov
Krishna Mullia
Zexiang Xu
Miloš Hašan
R. Ramamoorthi
63
36
0
06 Apr 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform
Achille Thin
Yazid Janati
Sylvain Le Corff
Charles Ollion
Arnaud Doucet
Alain Durmus
Eric Moulines
C. Robert
77
7
0
17 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
176
508
0
08 Mar 2021
Jacobian Determinant of Normalizing Flows
Huadong Liao
Jiawei He
DRL
47
8
0
12 Feb 2021
Neural BRDF Representation and Importance Sampling
Alejandro Sztrajman
G. Rainer
Tobias Ritschel
Tim Weyrich
38
60
0
11 Feb 2021
Copula Flows for Synthetic Data Generation
Sanket Kamthe
Samuel A. Assefa
M. Deisenroth
126
53
0
03 Jan 2021
Variational Determinant Estimation with Spherical Normalizing Flows
Simon Passenheim
Emiel Hoogeboom
BDL
48
1
0
24 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang
Ricky T. Q. Chen
Christos Tsirigotis
Aaron Courville
OT
211
98
0
10 Dec 2020
Discovering Pattern Structure Using Differentiable Compositing
P. Reddy
Paul Guerrero
Matthew Fisher
Wilmot Li
Miloy J. Mitra
68
29
0
17 Oct 2020
Deep Conditional Transformation Models
Philipp F. M. Baumann
Torsten Hothorn
David Rügamer
46
29
0
15 Oct 2020
Training Invertible Linear Layers through Rank-One Perturbations
Andreas Krämer
Jonas Köhler
Frank Noé
42
0
0
14 Oct 2020
Photon-Driven Neural Path Guiding
Shilin Zhu
Zexiang Xu
Tiancheng Sun
Alexandr Kuznetsov
Mark Meyer
H. Jensen
Hao Su
R. Ramamoorthi
18
0
0
05 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao
Karsten Kreis
Jan Kautz
Arash Vahdat
116
124
0
01 Oct 2020
Primary-Space Adaptive Control Variates using Piecewise-Polynomial Approximations
Miguel Crespo
Felix Bernal
A. Jarabo
A. Muñoz
28
9
0
15 Aug 2020
Invertible Neural BRDF for Object Inverse Rendering
Zhe Chen
S. Nobuhara
Ko Nishino
BDL
AI4CE
87
27
0
10 Aug 2020
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models
K. Nicoli
Christopher J. Anders
L. Funcke
T. Hartung
K. Jansen
Pan Kessel
Shinichi Nakajima
Paolo Stornati
AI4CE
58
3
0
14 Jul 2020
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows
Chris Cannella
Mohammadreza Soltani
Vahid Tarokh
BDL
55
0
0
13 Jul 2020
Black-box Adversarial Example Generation with Normalizing Flows
H. M. Dolatabadi
S. Erfani
C. Leckie
AAML
46
3
0
06 Jul 2020
Differentiable Rendering: A Survey
Hiroharu Kato
D. Beker
Mihai Morariu
Takahiro Ando
Toru Matsuoka
Wadim Kehl
Adrien Gaidon
3DH
3DV
92
175
0
22 Jun 2020
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