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Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
v1v2v3v4v5 (latest)

Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations

5 January 2025
Zaikang Lin
Sei Chang
Aaron Zweig
Minseo Kang
Elham Azizi
David A. Knowles
ArXiv (abs)PDFHTMLGithub (6224★)

Papers citing "Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations"

15 / 15 papers shown
Simulation-free Structure Learning for Stochastic Dynamics
Simulation-free Structure Learning for Stochastic Dynamics
Noah El Rimawi-Fine
Adam Stecklov
Lucas Nelson
Mathieu Blanchette
Alexander Tong
Stephen Y. Zhang
Lazar Atanackovic
AI4CE
193
1
0
18 Oct 2025
Residual-Informed Learning of Solutions to Algebraic Loops
Residual-Informed Learning of Solutions to Algebraic Loops
Felix Brandt
Andreas Heuermann
Philip Hannebohm
Bernhard Bachmann
115
0
0
10 Oct 2025
Physics-Informed Machine Learning in Biomedical Science and Engineering
Physics-Informed Machine Learning in Biomedical Science and Engineering
Nazanin Ahmadi
Qianying Cao
J. Humphrey
George Karniadakis
PINNAI4CE
216
3
0
06 Oct 2025
Learning Explicit Single-Cell Dynamics Using ODE Representations
Learning Explicit Single-Cell Dynamics Using ODE Representations
Jan-Philipp von Bassewitz
Adeel Pervez
Marco Fumero
Matthew Robinson
Theofanis Karaletsos
Francesco Locatello
PINNAI4CE
297
2
0
03 Oct 2025
Towards Identifiability of Interventional Stochastic Differential Equations
Towards Identifiability of Interventional Stochastic Differential Equations
Aaron Zweig
Zaikang Lin
Elham Azizi
David A. Knowles
469
1
0
21 May 2025
Causal machine learning for single-cell genomics
Causal machine learning for single-cell genomics
Alejandro Tejada-Lapuerta
Paul Bertin
Stefan Bauer
H. Aliee
Yoshua Bengio
Fabian J. Theis
CML
354
36
0
23 Oct 2023
Large-Scale Differentiable Causal Discovery of Factor Graphs
Large-Scale Differentiable Causal Discovery of Factor GraphsNeural Information Processing Systems (NeurIPS), 2022
Romain Lopez
Jan-Christian Hütter
J. Pritchard
Aviv Regev
CMLAI4CE
471
62
0
15 Jun 2022
Towards Causal Representation Learning
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OODCMLAI4CE
426
354
0
22 Feb 2021
Differentiable Causal Discovery from Interventional Data
Differentiable Causal Discovery from Interventional Data
P. Brouillard
Sébastien Lachapelle
Alexandre Lacoste
Damien Scieur
Alexandre Drouin
CML
482
251
0
03 Jul 2020
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
On Low Rank Directed Acyclic Graphs and Causal Structure LearningIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
Zhuangyan Fang
Shengyu Zhu
Jiji Zhang
Yue Liu
Zhitang Chen
Yangbo He
CML
370
39
0
10 Jun 2020
Interpolating between Optimal Transport and MMD using Sinkhorn
  Divergences
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences
Jean Feydy
Thibault Séjourné
François-Xavier Vialard
S. Amari
A. Trouvé
Gabriel Peyré
OT
475
651
0
18 Oct 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
1.6K
6,647
0
19 Jun 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng
Bryon Aragam
Pradeep Ravikumar
Eric Xing
NoLaCMLOffRL
560
1,261
0
04 Mar 2018
From Ordinary Differential Equations to Structural Causal Models: the
  deterministic case
From Ordinary Differential Equations to Structural Causal Models: the deterministic caseConference on Uncertainty in Artificial Intelligence (UAI), 2013
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
264
116
0
09 Aug 2014
Learning Module Networks
Learning Module NetworksJournal of machine learning research (JMLR), 2002
E. Segal
Dana Peér
Aviv Regev
D. Koller
N. Friedman
GNN
340
188
0
19 Oct 2012
1
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