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Jeremy Zucker
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All published works
Action
Title
Year
Authors
+
Perspectives for self-driving labs in synthetic biology
2023
Héctor García Martín
Tijana Radivojević
Jeremy Zucker
Kristofer E. Bouchard
Jess Sustarich
Sean Peisert
Dan Arnold
Nathan J. Hillson
G. Babnigg
Jose Manuel Martí
+
Do-calculus enables estimation of causal effects in partially observed biomolecular pathways
2022
Sara Mohammad-Taheri
Jeremy Zucker
Charles Tapley Hoyt
Karen Sachs
Vartika Tewari
Robert Osazuwa Ness
Olga Vitek
+
Perspectives for self-driving labs in synthetic biology
2022
Héctor García Martín
Tijana Radivojević
Jeremy Zucker
Kristofer E. Bouchard
Jess Sustarich
Sean Peisert
Dan Arnold
Nathan J. Hillson
G. Babnigg
Jose Manuel Martí
+
Experimental design for causal query estimation in partially observed biomolecular networks
2022
Sara Mohammad-Taheri
Vartika Tewari
Rohan Kapre
Ehsan Rahiminasab
Karen Sachs
Charles Tapley Hoyt
Jeremy Zucker
Olga Vitek
+
Do-calculus enables causal reasoning with latent variable models
2021
Sara Mohammad-Taheri
Robert Osazuwa Ness
Jeremy Zucker
Olga Vitek
+
PDF
Chat
Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis
2021
Jeremy Zucker
Kaushal Paneri
Sara Mohammad-Taheri
Somya Bhargava
Pallavi Kolambkar
Craig Bakker
Jeremy Teuton
Charles Tapley Hoyt
Kristie Oxford
Robert Osazuwa Ness
+
Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis
2021
Jeremy Zucker
Kaushal Paneri
Sara Mohammad-Taheri
Somya Bhargava
Pallavi Kolambkar
Craig Bakker
Jeremy Teuton
Charles Tapley Hoyt
Kristie Oxford
Robert Osazuwa Ness
+
Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis
2021
Jeremy Zucker
Kaushal Paneri
Sara Mohammad-Taheri
Somya Bhargava
Pallavi Kolambkar
Craig Bakker
Jeremy Teuton
Charles Tapley Hoyt
Kristie Oxford
Robert A. Van Ness
+
Do-calculus enables estimation of causal effects in partially observed biomolecular pathways
2021
Sara Mohammad-Taheri
Jeremy Zucker
Charles Tapley Hoyt
Karen Sachs
Vartika Tewari
Robert A. Van Ness
and Olga Vitek
Common Coauthors
Coauthor
Papers Together
Sara Mohammad-Taheri
7
Charles Tapley Hoyt
6
Olga Vitek
6
Robert Osazuwa Ness
4
Craig Bakker
3
Jeremy Teuton
3
Kristie Oxford
3
Vartika Tewari
3
Kaushal Paneri
3
Pallavi Kolambkar
3
Karen Sachs
3
Somya Bhargava
3
Tijana Radivojević
2
Deepanwita Banerjee
2
Nathan J. Hillson
2
Jess Sustarich
2
Sean Peisert
2
Blake A. Simmons
2
G. Babnigg
2
Héctor García Martín
2
James M. Carothers
2
Gregg T. Beckham
2
Deepti Tanjore
2
D. Agarwal
2
Tyler W. H. Backman
2
Lucas Waldburger
2
Lavanya Ramakrishnan
2
Kristofer E. Bouchard
2
Chris Mungall
2
ShivShankar Sundaram
2
Robert A. Van Ness
2
Anup K. Singh
2
Dan Arnold
2
Jose Manuel Martí
2
and Olga Vitek
1
Ehsan Rahiminasab
1
Rohan Kapre
1
Commonly Cited References
Action
Title
Year
Authors
# of times referenced
+
Exact stochastic simulation of coupled chemical reactions
1977
Daniel T. Gillespie
4
+
Stochastic variational inference
2013
Matthew D. Hoffman
David M. Blei
Chong Wang
John Paisley
3
+
PDF
Chat
Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
2011
Mark Girolami
Ben Calderhead
2
+
From Random Differential Equations to Structural Causal Models: the stochastic case
2018
Stephan Bongers
Joris M. Mooij
2
+
CORD-19: The COVID-19 Open Research Dataset
2020
Lucy Lu Wang
Kyle Lo
Yoganand Chandrasekhar
Russell Reas
Jiangjiang Yang
Darrin Eide
Kathryn Funk
Rodney Kinney
Ziyang Liu
William Merrill
2
+
Solving Differential Equations in<i>R</i>: Package<b>deSolve</b>
2010
Karline Soetaert
Thomas Petzoldt
R. Woodrow Setzer
2
+
Full Law Identification in Graphical Models of Missing Data: Completeness Results.
2020
Razieh Nabi
Rohit Bhattacharya
Ilya Shpitser
2
+
Causal diagrams for empirical research
1995
Judea Pearl
2
+
Identification and Estimation Of Causal Effects from Dependent Data.
2018
Eli Sherman
Ilya Shpitser
2
+
Pyro: Deep Universal Probabilistic Programming
2018
Eli Bingham
Jonathan P. Chen
Martin Jankowiak
Fritz Obermeyer
Neeraj Pradhan
Theofanis Karaletsos
Rohit Singh
Paul Szerlip
Paul Horsfall
Noah D. Goodman
2
+
PDF
Chat
Identifying Causal Effects with the <i>R</i> Package <b>causaleffect</b>
2017
Santtu Tikka
Juha Karvanen
2
+
Interventions and Causal Inference
2007
Frederick Eberhardt
Richard Scheines
2
+
PDF
Chat
Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis
2021
Jeremy Zucker
Kaushal Paneri
Sara Mohammad-Taheri
Somya Bhargava
Pallavi Kolambkar
Craig Bakker
Jeremy Teuton
Charles Tapley Hoyt
Kristie Oxford
Robert Osazuwa Ness
2
+
The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo
2014
Matthew D. Homan
Andrew Gelman
2
+
Pyro: Deep Universal Probabilistic Programming
2018
Eli Bingham
Jonathan P. Chen
Martin Jankowiak
Fritz Obermeyer
Neeraj Pradhan
Theofanis Karaletsos
Rohit Singh
Paul Szerlip
Paul Horsfall
Noah D. Goodman
2
+
PDF
Chat
The Blessings of Multiple Causes
2019
Zhaoran Wang
David M. Blei
2
+
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
2019
Robert Osazuwa Ness
Kaushal Paneri
Olga Vitek
2
+
PDF
Chat
Exploring behaviors of stochastic differential equation models of biological systems using change of measures
2012
Sumit Kumar Jha
Christopher J. Langmead
2
+
PDF
Chat
Chain Graph Models and their Causal Interpretations
2002
Steffen L. Lauritzen
Thomas S. Richardson
2
+
PDF
Chat
Causal inference and the data-fusion problem
2016
Elias Bareinboim
Judea Pearl
2
+
PDF
Chat
Graphical methods for inequality constraints in marginalized DAGs
2012
Robin J. Evans
1
+
PDF
Chat
A Bayesian machine scientist to aid in the solution of challenging scientific problems
2020
Roger Guimerà
I. Reichardt
Antoni Aguilar‐Mogas
Francesco Alessandro Massucci
Manuel Miranda
Jordi Pallarès
Marta Sales‐Pardo
1
+
Estimation of causal effects with small data under implicit functional constraints
2020
Jouni Helske
Santtu Tikka
Juha Karvanen
1
+
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables
2020
Rohit Bhattacharya
Razieh Nabi
Ilya Shpitser
1
+
Identification Methods With Arbitrary Interventional Distributions as Inputs
2020
Jaron J. R. Lee
Ilya Shpitser
1
+
Full Law Identification In Graphical Models Of Missing Data: Completeness Results
2020
Razieh Nabi
Rohit Bhattacharya
Ilya Shpitser
1
+
PDF
Chat
Self-driving laboratory for accelerated discovery of thin-film materials
2020
Benjamin P. MacLeod
Fraser G. L. Parlane
Thomas D. Morrissey
Florian Häse
Loı̈c M. Roch
Kevan E. Dettelbach
Raphaell Moreira
Lars P. E. Yunker
Michael B. Rooney
Joseph R. Deeth
1
+
Estimation of causal effects with small data in the presence of trapdoor variables
2020
Jouni Helske
Santtu Tikka
Juha Karvanen
1
+
PDF
Chat
Machine Learning Conservation Laws from Trajectories
2021
Ziming Liu
Max Tegmark
1
+
Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning
2020
Adarsh Dave
Jared Mitchell
Kirthevasan Kandasamy
Han Wang
Sven Burke
Biswajit Paria
Barnabás Póczos
Jay Whitacre
Venkatasubramanian Viswanathan
1
+
Learning Causal Effects via Weighted Empirical Risk Minimization
2020
Yonghan Jung
Jin Tian
Elias Bareinboim
1
+
Physics-informed neural networks (PINNs) for fluid mechanics: a review
2021
Shengze Cai
Zhiping Mao
Zhicheng Wang
Minglang Yin
George Em Karniadakis
1
+
Gibbs Sampling
2000
Alan E. Gelfand
1
+
Full Law Identification In Graphical Models Of Missing Data: Completeness Results
2020
Razieh Nabi
Rohit Bhattacharya
Ilya Shpitser
1
+
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
2019
Robert Osazuwa Ness
Kaushal Paneri
Olga Vitek
1
+
Beyond Structural Causal Models: Causal Constraints Models
2018
Tineke Blom
Stephan Bongers
Joris M. Mooij
1
+
Stochastic Variational Inference
2012
Matt Hoffman
David M. Blei
Chong Wang
John Paisley
1
+
Identification of joint interventional distributions in recursive semi-Markovian causal models
2006
Ilya Shpitser
Judea Pearl
1
+
Neurosymbolic AI: The 3rd Wave
2020
Artur S. d’Avila Garcez
Luís C. Lamb
1
+
PDF
Chat
Graphs for Margins of Bayesian Networks
2015
Robin J. Evans
1
+
Stochastic Gradient VB and the Variational Auto-Encoder
2013
Diederik P. Kingma
Max Welling
1
+
The Markov chain Monte Carlo method: an approach to approximate counting and integration
1996
Mark Jerrum
Alistair Sinclair
1
+
Pearl's Calculus of Intervention Is Complete
2012
Yimin Huang
Marco Valtorta
1
+
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models.
2014
Danilo Jimenez Rezende
Shakir Mohamed
Daan Wierstra
1
+
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
2014
Danilo Jimenez Rezende
Shakir Mohamed
Daan Wierstra
1
+
PDF
Chat
Targeted Maximum Likelihood Learning
2006
Mark J. van der Laan
Daniel B. Rubin
1
+
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
1986
James M. Robins
1
+
PDF
Chat
Measurement bias and effect restoration in causal inference
2014
Manabu Kuroki
J. Pearl
1
+
Complete Identification Methods for the Causal Hierarchy
2008
Ilya Shpitser
Judea Pearl
1
+
Doubly Robust Estimation in Missing Data and Causal Inference Models
2005
Heejung Bang
James M. Robins
1