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. 2306.14861
  4. Cited By
Leveraging Task Structures for Improved Identifiability in Neural
  Network Representations
v1v2 (latest)

Leveraging Task Structures for Improved Identifiability in Neural Network Representations

26 June 2023
Jiajun He
Julien Horwood
Juyeon Heo
José Miguel Hernández-Lobato
    CML
ArXiv (abs)PDFHTML

Papers citing "Leveraging Task Structures for Improved Identifiability in Neural Network Representations"

18 / 18 papers shown
Title
Identifiability of deep generative models without auxiliary information
Identifiability of deep generative models without auxiliary information
Bohdan Kivva
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
DRL
94
52
0
20 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse
  Mechanism Shift Hypothesis
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Ronan Perry
Julius von Kügelgen
Bernhard Schölkopf
93
50
0
04 Jun 2022
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular
  Property Prediction
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction
Jiajun He
Austin Tripp
José Miguel Hernández-Lobato
56
23
0
05 May 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko
Pavel Izmailov
A. Wilson
OOD
86
339
0
06 Apr 2022
Disentanglement via Mechanism Sparsity Regularization: A New Principle
  for Nonlinear ICA
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
Sébastien Lachapelle
Pau Rodríguez López
Yash Sharma
Katie Everett
Rémi Le Priol
Alexandre Lacoste
Simon Lacoste-Julien
CMLOOD
90
140
0
21 Jul 2021
Disentangling Identifiable Features from Noisy Data with Structured
  Nonlinear ICA
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA
Hermanni Hälvä
Sylvain Le Corff
Luc Lehéricy
Jonathan So
Yongjie Zhu
Elisabeth Gassiat
Aapo Hyvarinen
CML
60
65
0
17 Jun 2021
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
M. Willetts
Brooks Paige
CMLOOD
46
25
0
09 Jun 2021
E(n) Equivariant Graph Neural Networks
E(n) Equivariant Graph Neural Networks
Victor Garcia Satorras
Emiel Hoogeboom
Max Welling
113
1,033
0
19 Feb 2021
On Linear Identifiability of Learned Representations
On Linear Identifiability of Learned Representations
Geoffrey Roeder
Luke Metz
Diederik P. Kingma
CML
60
85
0
01 Jul 2020
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on
  Nonlinear ICA
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
Ilyes Khemakhem
R. Monti
Diederik P. Kingma
Aapo Hyvarinen
CML
81
114
0
26 Feb 2020
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
195
2,242
0
05 Jul 2019
Graph Normalizing Flows
Graph Normalizing Flows
Jenny Liu
Aviral Kumar
Jimmy Ba
J. Kiros
Kevin Swersky
BDLGNNAI4CE
74
165
0
30 May 2019
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive
  Learning
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning
Aapo Hyvarinen
Hiroaki Sasaki
Richard Turner
OODCML
97
331
0
22 May 2018
GraphVAE: Towards Generation of Small Graphs Using Variational
  Autoencoders
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders
M. Simonovsky
N. Komodakis
GNNBDL
120
853
0
09 Feb 2018
A Review on Bilevel Optimization: From Classical to Evolutionary
  Approaches and Applications
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications
Ankur Sinha
P. Malo
Kalyanmoy Deb
46
758
0
17 May 2017
Variational Graph Auto-Encoders
Variational Graph Auto-Encoders
Thomas Kipf
Max Welling
GNNBDLSSLCML
153
3,592
0
21 Nov 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing
  Generative Adversarial Nets
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
161
4,238
0
12 Jun 2016
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OODSSL
278
12,458
0
24 Jun 2012
1