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2112.02761
Cited By
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
6 December 2021
Chris Cundy
Aditya Grover
Stefano Ermon
CML
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Papers citing
"BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery"
15 / 15 papers shown
Title
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs
Ryan Thompson
Edwin V. Bonilla
Robert Kohn
31
0
0
24 May 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth
Christian Knoll
Franz Pernkopf
Robert Peharz
CML
43
1
0
22 Feb 2024
Order-based Structure Learning with Normalizing Flows
Hamidreza Kamkari
Vahid Balazadeh Meresht
Vahid Zehtab
Rahul G. Krishnan
CML
23
1
0
14 Aug 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Chris C. Emezue
Alexandre Drouin
T. Deleu
Stefan Bauer
Yoshua Bengio
CML
24
2
0
11 Jul 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
T. Deleu
Mizu Nishikawa-Toomey
Jithendaraa Subramanian
Nikolay Malkin
Laurent Charlin
Yoshua Bengio
BDL
28
43
0
30 May 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
Yuxiao Cheng
Lianglong Li
Tingxiong Xiao
Zongren Li
Qionghai Dai
J. Suo
K. He
CML
BDL
AI4TS
21
21
0
10 May 2023
A theory of continuous generative flow networks
Salem Lahlou
T. Deleu
Pablo Lemos
Dinghuai Zhang
Alexandra Volokhova
Alex Hernández-García
Léna Néhale Ezzine
Yoshua Bengio
Nikolay Malkin
AI4CE
24
79
0
30 Jan 2023
DAG Learning on the Permutahedron
Valentina Zantedeschi
Luca Franceschi
Jean Kaddour
Matt J. Kusner
Vlad Niculae
25
11
0
27 Jan 2023
Trust Your
∇
\nabla
∇
: Gradient-based Intervention Targeting for Causal Discovery
Mateusz Olko
Michal Zajac
A. Nowak
Nino Scherrer
Yashas Annadani
Stefan Bauer
Lukasz Kucinski
Piotr Milos
CML
22
2
0
24 Nov 2022
On the Generalization and Adaption Performance of Causal Models
Nino Scherrer
Anirudh Goyal
Stefan Bauer
Yoshua Bengio
Nan Rosemary Ke
CML
OOD
BDL
TTA
23
8
0
09 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions
Alexander Hagele
Jonas Rothfuss
Lars Lorch
Vignesh Ram Somnath
Bernhard Schölkopf
Andreas Krause
CML
BDL
31
19
0
03 Jun 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale
P. Tigas
Yashas Annadani
Andrew Jesson
Bernhard Schölkopf
Y. Gal
Stefan Bauer
CML
26
48
0
03 Mar 2022
Bayesian Structure Learning with Generative Flow Networks
T. Deleu
António Góis
Chris C. Emezue
M. Rankawat
Simon Lacoste-Julien
Stefan Bauer
Yoshua Bengio
BDL
31
143
0
28 Feb 2022
Learning Neural Causal Models with Active Interventions
Nino Scherrer
O. Bilaniuk
Yashas Annadani
Anirudh Goyal
Patrick Schwab
Bernhard Schölkopf
Michael C. Mozer
Yoshua Bengio
Stefan Bauer
Nan Rosemary Ke
CML
28
42
0
06 Sep 2021
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks
Dennis L. Wei
Tian Gao
Yue Yu
CML
56
71
0
18 Oct 2020
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