ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1503.03167
  4. Cited By
Deep Convolutional Inverse Graphics Network

Deep Convolutional Inverse Graphics Network

11 March 2015
Tejas D. Kulkarni
William F. Whitney
Pushmeet Kohli
J. Tenenbaum
    DRL
    BDL
ArXivPDFHTML

Papers citing "Deep Convolutional Inverse Graphics Network"

20 / 20 papers shown
Title
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research
Patrik Reizinger
Randall Balestriero
David Klindt
Wieland Brendel
139
0
0
17 Apr 2025
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Konstantin Donhauser
Kristina Ulicna
Gemma Elyse Moran
Aditya Ravuri
Kian Kenyon-Dean
Cian Eastwood
Jason Hartford
127
0
0
20 Dec 2024
Disentanglement Learning via Topology
Disentanglement Learning via Topology
Nikita Balabin
Daria Voronkova
I. Trofimov
Evgeny Burnaev
S. Barannikov
DRL
101
3
0
24 Aug 2023
MVTN: Learning Multi-View Transformations for 3D Understanding
MVTN: Learning Multi-View Transformations for 3D Understanding
Abdullah Hamdi
Faisal AlZahrani
Silvio Giancola
Guohao Li
3DV
3DPC
104
6
0
27 Dec 2022
Deep Structural Causal Models for Tractable Counterfactual Inference
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski
Daniel Coelho De Castro
Ben Glocker
CML
MedIm
101
237
0
11 Jun 2020
Weakly Supervised Disentanglement with Guarantees
Weakly Supervised Disentanglement with Guarantees
Rui Shu
Yining Chen
Abhishek Kumar
Stefano Ermon
Ben Poole
CoGe
DRL
114
137
0
22 Oct 2019
Disentangled Representations in Neural Models
Disentangled Representations in Neural Models
William F. Whitney
OOD
OCL
DRL
103
18
0
07 Feb 2016
MatConvNet - Convolutional Neural Networks for MATLAB
MatConvNet - Convolutional Neural Networks for MATLAB
Andrea Vedaldi
Karel Lenc
320
2,945
0
15 Dec 2014
Learning to Generate Chairs, Tables and Cars with Convolutional Networks
Learning to Generate Chairs, Tables and Cars with Convolutional Networks
Alexey Dosovitskiy
Jost Tobias Springenberg
Maxim Tatarchenko
Thomas Brox
GAN
170
676
0
21 Nov 2014
Inverse Graphics with Probabilistic CAD Models
Inverse Graphics with Probabilistic CAD Models
Tejas D. Kulkarni
Vikash K. Mansinghka
Pushmeet Kohli
J. Tenenbaum
3DV
72
19
0
04 Jul 2014
Variational Particle Approximations
Variational Particle Approximations
A. Saeedi
Tejas D. Kulkarni
Vikash K. Mansinghka
S. Gershman
148
60
0
24 Feb 2014
The Informed Sampler: A Discriminative Approach to Bayesian Inference in
  Generative Computer Vision Models
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models
Varun Jampani
Sebastian Nowozin
M. Loper
Peter V. Gehler
95
45
0
04 Feb 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
452
16,933
0
20 Dec 2013
Approximate Bayesian Image Interpretation using Generative Probabilistic
  Graphics Programs
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
Vikash K. Mansinghka
Tejas D. Kulkarni
Yura N. Perov
J. Tenenbaum
175
108
0
29 Jun 2013
Deep Generative Stochastic Networks Trainable by Backprop
Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio
Eric Thibodeau-Laufer
Guillaume Alain
J. Yosinski
BDL
128
396
0
05 Jun 2013
Disentangling Factors of Variation via Generative Entangling
Disentangling Factors of Variation via Generative Entangling
Guillaume Desjardins
Aaron Courville
Yoshua Bengio
CoGe
CML
DRL
90
104
0
19 Oct 2012
Deep Lambertian Networks
Deep Lambertian Networks
Yichuan Tang
Ruslan Salakhutdinov
Geoffrey E. Hinton
GAN
CVBM
63
84
0
27 Jun 2012
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
256
12,435
0
24 Jun 2012
Elliptical slice sampling
Elliptical slice sampling
Iain Murray
Ryan P. Adams
D. MacKay
124
465
0
31 Dec 2009
Approximate Bayesian computation (ABC) gives exact results under the
  assumption of model error
Approximate Bayesian computation (ABC) gives exact results under the assumption of model error
Richard D. Wilkinson
104
273
0
20 Nov 2008
1