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. 2112.12982
  4. Cited By
Parameter identifiability of a deep feedforward ReLU neural network

Parameter identifiability of a deep feedforward ReLU neural network

24 December 2021
Joachim Bona-Pellissier
François Bachoc
François Malgouyres
ArXivPDFHTML

Papers citing "Parameter identifiability of a deep feedforward ReLU neural network"

13 / 13 papers shown
Title
Finite Samples for Shallow Neural Networks
Finite Samples for Shallow Neural Networks
Yu Xia
Zhiqiang Xu
41
0
0
17 Mar 2025
Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction
  of Black-Box Neural Networks
Sequencing the Neurome: Towards Scalable Exact Parameter Reconstruction of Black-Box Neural Networks
Judah Goldfeder
Quinten Roets
Gabe Guo
John Wright
Hod Lipson
28
1
0
27 Sep 2024
Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery
Daniel Waxman
Kurt Butler
P. Djuric
23
3
0
05 Jan 2024
Copula-Based Deep Survival Models for Dependent Censoring
Copula-Based Deep Survival Models for Dependent Censoring
Ali Hossein Gharari Foomani
Michael Cooper
Russell Greiner
Rahul G. Krishnan
12
10
0
20 Jun 2023
Exploring the Complexity of Deep Neural Networks through Functional
  Equivalence
Exploring the Complexity of Deep Neural Networks through Functional Equivalence
Guohao Shen
22
2
0
19 May 2023
Functional Equivalence and Path Connectivity of Reducible Hyperbolic
  Tangent Networks
Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks
Matthew Farrugia-Roberts
8
4
0
08 May 2023
Expand-and-Cluster: Parameter Recovery of Neural Networks
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli
Berfin Simsek
W. Gerstner
Johanni Brea
19
4
0
25 Apr 2023
Towards Efficient MCMC Sampling in Bayesian Neural Networks by
  Exploiting Symmetry
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
J. G. Wiese
Lisa Wimmer
Theodore Papamarkou
Bernd Bischl
Stephan Günnemann
David Rügamer
14
11
0
06 Apr 2023
Local Identifiability of Deep ReLU Neural Networks: the Theory
Local Identifiability of Deep ReLU Neural Networks: the Theory
Joachim Bona-Pellissier
Franccois Malgouyres
F. Bachoc
FAtt
47
6
0
15 Jun 2022
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer
  Neural Network
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
Mo Zhou
Rong Ge
Chi Jin
69
44
0
04 Feb 2021
Cryptanalytic Extraction of Neural Network Models
Cryptanalytic Extraction of Neural Network Models
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
FedML
MLAU
MIACV
AAML
65
134
0
10 Mar 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,830
0
08 Jul 2016
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
228
31,150
0
16 Jan 2013
1