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Assessing the overall and partial causal well-specification of nonlinear
  additive noise models
v1v2v3 (latest)

Assessing the overall and partial causal well-specification of nonlinear additive noise models

25 October 2023
Christoph Schultheiss
Peter Bühlmann
    CML
ArXiv (abs)PDFHTML

Papers citing "Assessing the overall and partial causal well-specification of nonlinear additive noise models"

15 / 15 papers shown
Title
Achievable distributional robustness when the robust risk is only partially identified
Achievable distributional robustness when the robust risk is only partially identified
Julia Kostin
Nicola Gnecco
Fanny Yang
128
3
0
04 Feb 2025
CausalBench: A Large-scale Benchmark for Network Inference from
  Single-cell Perturbation Data
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data
Mathieu Chevalley
Yusuf Roohani
Arash Mehrjou
J. Leskovec
Patrick Schwab
CML
87
38
0
31 Oct 2022
On the Identifiability and Estimation of Causal Location-Scale Noise
  Models
On the Identifiability and Estimation of Causal Location-Scale Noise Models
Alexander Immer
Christoph Schultheiss
Julia E. Vogt
Bernhard Schölkopf
Peter Buhlmann
Alexander Marx
CML
82
36
0
13 Oct 2022
Identifying Patient-Specific Root Causes with the Heteroscedastic Noise
  Model
Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model
Eric V. Strobl
Thomas A. Lasko
CML
117
35
0
25 May 2022
Generalizing to Unseen Domains: A Survey on Domain Generalization
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang
Cuiling Lan
Chang-Shu Liu
Yidong Ouyang
Tao Qin
Wang Lu
Yiqiang Chen
Wenjun Zeng
Philip S. Yu
OOD
231
1,233
0
02 Mar 2021
A simple measure of conditional dependence
A simple measure of conditional dependence
Mona Azadkia
S. Chatterjee
151
131
0
27 Oct 2019
The Hardness of Conditional Independence Testing and the Generalised
  Covariance Measure
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure
Rajen Dinesh Shah
J. Peters
152
303
0
19 Apr 2018
Kernel-based Tests for Joint Independence
Kernel-based Tests for Joint Independence
Niklas Pfister
Peter Buhlmann
Bernhard Schölkopf
J. Peters
62
186
0
01 Mar 2016
Causal inference using invariant prediction: identification and
  confidence intervals
Causal inference using invariant prediction: identification and confidence intervals
J. Peters
Peter Buhlmann
N. Meinshausen
OOD
124
974
0
06 Jan 2015
On the Intersection Property of Conditional Independence and its
  Application to Causal Discovery
On the Intersection Property of Conditional Independence and its Application to Causal Discovery
J. Peters
CML
64
30
0
03 Mar 2014
CAM: Causal additive models, high-dimensional order search and penalized
  regression
CAM: Causal additive models, high-dimensional order search and penalized regression
Peter Buhlmann
J. Peters
J. Ernest
CML
129
325
0
06 Oct 2013
Causal Discovery with Continuous Additive Noise Models
Causal Discovery with Continuous Additive Noise Models
Jonas Peters
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
CML
116
573
0
26 Sep 2013
The Do-Calculus Revisited
The Do-Calculus Revisited
Judea Pearl
CML
143
167
0
16 Oct 2012
Variable selection with error control: Another look at Stability
  Selection
Variable selection with error control: Another look at Stability Selection
Rajen Dinesh Shah
R. Samworth
93
357
0
27 May 2011
P-values for high-dimensional regression
P-values for high-dimensional regression
N. Meinshausen
L. Meier
Peter Buhlmann
125
441
0
13 Nov 2008
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