Biased Stochastic FirstOrder Methods for Conditional Stochastic Optimization and Applications in Meta Learning
Yifan Hu
•
Siqi Zhang
•
Xin Chen
•
Niao He

20201201

Causal Estimation with Functional Confounders
Aahlad Manas Puli
•
Adler Perotte
•
Rajesh Ranganath

20201201

General Transportability of Soft Interventions: Completeness Results
Juan Correa
•
Elias Bareinboim

20201201

Learning Causal Effects via Weighted Empirical Risk Minimization
Yonghan Jung
•
Jin Tian
•
Elias Bareinboim

20201201

Adversarial Counterfactual Learning and Evaluation for Recommender System
Da Xu
•
Chuanwei Ruan
•
Evren Korpeoglu
•
Sushant Kumar
•
Kannan Achan

20201201

Entropic Causal Inference: Identifiability and Finite Sample Results
Spencer Compton
•
Murat Kocaoglu
•
Kristjan Greenewald
•
Dmitriy Katz

20201201

Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects
Zijun Gao
•
Yanjun Han

20201201

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
Hyemi Kim
•
Seungjae Shin
•
JoonHo Jang
•
Kyungwoo Song
•
Weonyoung Joo
•
Wanmo Kang
•
IlChul Moon

20201124

Invariant Representation Learning for Treatment Effect Estimation
Claudia Shi
•
Victor Veitch
•
David Blei

20201124

A systematic review of causal methods enabling predictions under hypothetical interventions
Lijing Lin
•
Matthew Sperrin
•
David A. Jenkins
•
Glen P. Martin
•
Niels Peek

20201119

SplitTreatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions

Yanbo Xu
•
Divyat Mahajan
•
Liz Manrao
•
Amit Sharma
•
Emre Kiciman

20201111

Teaching deep learning causal effects improves predictive performance
Jia Li
•
Xiaowei Jia
•
HaoYu Yang
•
Vipin Kumar
•
Michael Steinbach
•
Gyorgy Simon

20201111

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
Ramaravind K. Mothilal
•
Divyat Mahajan
•
Chenhao Tan
•
Amit Sharma

20201110

DoWhy: An EndtoEnd Library for Causal Inference

Amit Sharma
•
Emre Kiciman

20201109

Causal Autoregressive Flows
Ilyes Khemakhem
•
Ricardo Pio Monti
•
Robert Leech
•
Aapo Hyvärinen

20201104

Doubly Robust OffPolicy Learning on LowDimensional Manifolds by Deep Neural Networks
Minshuo Chen
•
Hao liu
•
Wenjing Liao
•
Tuo Zhao

20201103

Causal CampbellGoodhart's law and Reinforcement Learning

Hal Ashton

20201102

Structural Causal Model with Expert Augmented Knowledge to Estimate the Effect of Oxygen Therapy on Mortality in the ICU
Md Osman Gani
•
Shravan Kethireddy
•
Marvi Bikak
•
Paul Griffin
•
Mohammad Adibuzzaman

20201028

CaMGen:Causallyaware Metricguided Text Generation
Navita Goyal
•
Roodram Paneri
•
Ayush Agarwal
•
Udit Kalani
•
Abhilasha Sancheti
•
Niyati Chhaya

20201024

Counterfactual Representation Learning with Balancing Weights
Serge Assaad
•
Shuxi Zeng
•
Chenyang Tao
•
Shounak Datta
•
Nikhil Mehta
•
Ricardo Henao
•
Fan Li
•
Lawrence Carin

20201023

Causal Discovery using CompressionComplexity Measures

Pranay SY
•
Nithin Nagaraj

20201019

Poincare: Recommending Publication Venues via Treatment Effect Estimation
Ryoma Sato
•
Makoto Yamada
•
Hisashi Kashima

20201019

Causal Inference in the Presence of Interference in Sponsored Search Advertising
Razieh Nabi
•
Joel Pfeiffer
•
Murat Ali Bayir
•
Denis Charles
•
Emre Kiciman

20201015

Causal MultiLevel Fairness
Vishwali Mhasawade
•
Rumi Chunara

20201014

Causal Feature Selection with Dimension Reduction for Interpretable Text Classification
Guohou Shan
•
James Foulds
•
SHimei Pan

20201009

On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable
Yifan Cui
•
Eric Tchetgen Tchetgen

20201007

Using Experimental Data to Evaluate Methods for Observational Causal Inference
Amanda Gentzel
•
Justin Clarke
•
David Jensen

20201006

LongTailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect

Kaihua Tang
•
Jianqiang Huang
•
Hanwang Zhang

20200928

Targeted VAE: Structured Inference and Targeted Learning for Causal Parameter Estimation
Matthew James Vowels
•
Necati Cihan Camgoz
•
Richard Bowden

20200928

Causal Intervention for WeaklySupervised Semantic Segmentation

Dong Zhang
•
Hanwang Zhang
•
Jinhui Tang
•
XianSheng Hua
•
Qianru Sun

20200926

Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference
Galen Weld
•
Peter West
•
Maria Glenski
•
David Arbour
•
Ryan Rossi
•
Tim Althoff

20200921

Hidden Latent State Inference in a SpatioTemporal Generative Model
Matthias Karlbauer
•
Tobias Menge
•
Sebastian Otte
•
Hendrik P. A. Lensch
•
Thomas Scholten
•
Volker Wulfmeyer
•
Martin V. Butz

20200921

Chemical Property Prediction Under Experimental Biases
Yang Liu
•
Hisashi Kashima

20200918

Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework

Kunwoo Park
•
Haewoon Kwak
•
Jisun An
•
Sanjay Chawla

20200917

Estimating Individual Treatment Effects using NonParametric Regression Models: a Review
Alberto Caron
•
Ioanna Manolopoulou
•
Gianluca Baio

20200914

Semisupervised learning and the question of true versus estimated propensity scores
Andrew Herren
•
P. Richard Hahn

20200914

Quantifying the Causal Effects of Conversational Tendencies
Justine Zhang
•
Sendhil Mullainathan
•
Cristian DanescuNiculescuMizil

20200908

Causal Inference in Possibly Nonlinear Factor Models
Yingjie Feng

20200831

Path Dependent Structural Equation Models
Ranjani Srinivasan
•
Jaron Lee
•
Rohit Bhattacharya
•
Narges Ahmidi
•
Ilya Shpitser

20200824

HiCI: Deep Causal Inference in High Dimensions
Ankit Sharma
•
Garima Gupta
•
Ranjitha Prasad
•
Arnab Chatterjee
•
Lovekesh Vig
•
Gautam Shroff

20200822

LongTerm Effect Estimation with Surrogate Representation
Lu Cheng
•
Ruocheng Guo
•
Huan Liu

20200819

Estimation of causal effects of multiple treatments in healthcare database studies with rare outcomes
Liangyuan Hu
•
Chenyang Gu

20200818

Estimating Causal Effects with the Neural Autoregressive Density Estimator
Sergio Garrido
•
Stanislav S. Borysov
•
Jeppe Rich
•
Francisco C. Pereira

20200817

Estimating heterogeneous survival treatment effect in observational data using machine learning

Liangyuan Hu
•
Jiayi Ji
•
Fan Li

20200817

Structural Causal Models Are (Solvable by) Credal Networks

Marco Zaffalon
•
Alessandro Antonucci
•
Rafael Cabañas

20200802

Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding
Justin Grimmer
•
Dean Knox
•
Brandon M. Stewart

20200724

Computational Causal Inference
Jeffrey C. Wong

20200721

Autoregressive flowbased causal discovery and inference

Ricardo Pio Monti
•
Ilyes Khemakhem
•
Aapo Hyvarinen

20200718

When deep learning meets causal inference: a computational framework for drug repurposing from realworld data

Ruoqi Liu
•
Lai Wei
•
Ping Zhang

20200716

Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty
•
Kenta Takatsu
•
David Jensen
•
Vikash Mansinghka

20200714

Learning to search efficiently for causally nearoptimal treatments
Samuel Håkansson
•
Viktor Lindblom
•
Omer Gottesman
•
Fredrik D. Johansson

20200702

A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model
Riddhiman Adib
•
Paul Griffin
•
Sheikh Iqbal Ahamed
•
Mohammad Adibuzzaman

20200622

Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org
Soumajyoti Sarkar
•
Hamidreza Alvari

20200620

Disentangling User Interest and Popularity Bias for Recommendation with Causal Embedding

Yu Zheng
•
Chen Gao
•
Xiang Li
•
Xiangnan He
•
Yong Li
•
Depeng Jin

20200619

Causal intersectionality for fair ranking

Ke Yang
•
Joshua R. Loftus
•
Julia Stoyanovich

20200615

Learning Individually Inferred Communication for MultiAgent Cooperation
Ziluo Ding
•
Tiejun Huang
•
Zongqing Lu

20200611

Regret Minimization for Causal Inference on Large Treatment Space
Akira Tanimoto
•
Tomoya Sakai
•
Takashi Takenouchi
•
Hisashi Kashima

20200610

Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects

Qiming Du
•
Gérard Biau
•
François Petit
•
Raphaël Porcher

20200608

Identifying Causal Structure in Dynamical Systems

Dominik Baumann
•
Friedrich Solowjow
•
Karl H. Johansson
•
Sebastian Trimpe

20200606

Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains
James Bannon
•
Brad Windsor
•
Wenbo Song
•
Tao Li

20200603

Navigated Weighting to Improve Inverse Probability Weighting for Missing Data Problems and Causal Inference
Hiroto Katsumata

20200522

Studying Product Competition Using Representation Learning
Fanglin Chen
•
Xiao Liu
•
Davide Proserpio
•
Isamar Troncoso
•
Feiyu Xiong

20200521

Principal Fairness for Human and Algorithmic DecisionMaking
Kosuke Imai
•
Zhichao Jiang

20200521

Automatic Detection of Influential Actors in Disinformation Networks
Steven T. Smith
•
Edward K. Kao
•
Erika D. Mackin
•
Danelle C. Shah
•
Olga Simek
•
Donald B. Rubin

20200521

Causal Modeling of Twitter Activity During COVID19

Oguzhan Gencoglu
•
Mathias Gruber

20200516

A theoretical treatment of conditional independence testing under ModelX
Eugene Katsevich
•
Aaditya Ramdas

20200512

Counterfactual Propagation for SemiSupervised Individual Treatment Effect Estimation
Shonosuke Harada
•
Hisashi Kashima

20200511

ConstraintBased Causal Discovery using Partial Ancestral Graphs in the presence of Cycles
Joris M. Mooij
•
Tom Claassen

20200501

Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series

Erik Scharwächter
•
Emmanuel Müller

20200430

Causal Modeling with Stochastic Confounders
Thanh Vinh Vo
•
Pengfei Wei
•
Wicher Bergsma
•
TzeYun Leong

20200424

Machine learning for causal inference: on the use of crossfit estimators
Paul N Zivich
•
Alexander Breskin

20200421

Causal Inference in CaseControl Studies

Sung Jae Jun
•
Sokbae Lee

20200417

A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric Approaches

Arman Oganisian
•
Jason A. Roy

20200415

A category theoretical argument for causal inference
Rémy Tuyéras

20200409

Causal Relational Learning
Babak Salimi
•
Harsh Parikh
•
Moe Kayali
•
Sudeepa Roy
•
Lise Getoor
•
Dan Suciu

20200407

ParKCa: Causal Inference with Partially Known Causes

Raquel Aoki
•
Martin Ester

20200317

Invariant Causal Prediction for Block MDPs

Amy Zhang
•
Clare Lyle
•
Shagun Sodhani
•
Angelos Filos
•
Marta Kwiatkowska
•
Joelle Pineau
•
Yarin Gal
•
Doina Precup

20200312

Towards Clarifying the Theory of the Deconfounder
Yixin Wang
•
David M. Blei

20200310

Who Make Drivers Stop? Towards Drivercentric Risk Assessment: Risk Object Identification via Causal Inference
Chengxi Li
•
Stanley H. Chan
•
YiTing Chen

20200305

Sense and Sensitivity Analysis: Simple PostHoc Analysis of Bias Due to Unobserved Confounding

Victor Veitch
•
Anisha Zaveri

20200303

Unbiased Scene Graph Generation from Biased Training

Kaihua Tang
•
Yulei Niu
•
Jianqiang Huang
•
Jiaxin Shi
•
Hanwang Zhang

20200227

MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models

Imke Mayer
•
Julie Josse
•
Félix Raimundo
•
JeanPhilippe Vert

20200225

Biased Stochastic Gradient Descent for Conditional Stochastic Optimization
Yifan Hu
•
Siqi Zhang
•
Xin Chen
•
Niao He

20200225

CausalML: Python Package for Causal Machine Learning

Huigang Chen
•
Totte Harinen
•
JeongYoon Lee
•
Mike Yung
•
Zhenyu Zhao

20200225

Fairness through Experimentation: Inequality in A/B testing as an approach to responsible design
Guillaume SaintJacques
•
Amir Sepehri
•
Nicole Li
•
Igor Perisic

20200214

Causality in cognitive neuroscience: concepts, challenges, and distributional robustness
Sebastian Weichwald
•
Jonas Peters

20200214

Causal analysis of competing atomistic mechanisms in ferroelectric materials from highresolution Scanning Transmission Electron Microscopy data
Maxim Ziatdinov
•
Chris Nelson
•
Xiaohang Zhang
•
Rama Vasudevan
•
Eugene Eliseev
•
Anna N. Morozovska
•
Ichiro Takeuchi
•
Sergei V. Kalinin

20200211

Simulating longitudinal data from marginal structural models using the additive hazard model
Ruth H. Keogh
•
Shaun R. Seaman
•
Jon Michael Gran
•
Stijn Vansteelandt

20200210

On Geometry of Information Flow for Causal Inference
Sudam Surasinghe
•
Erik M. Bollt

20200206

A Survey on Causal Inference
Liuyi Yao
•
Zhixuan Chu
•
Sheng Li
•
Yaliang Li
•
Jing Gao
•
Aidong Zhang

20200205

Variablelag Granger Causality and Transfer Entropy for Time Series Analysis

Chainarong Amornbunchornvej
•
Elena Zheleva
•
Tanya BergerWolf

20200201

Inferring Individual Level Causal Models from Graphbased Relational Time Series
Ryan Rossi
•
Somdeb Sarkhel
•
Nesreen Ahmed

20200116

Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision
Li Ye
•
Yishi Lin
•
Hong Xie
•
John C. S. Lui

20200116

Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond

Nathan Kallus
•
Xiaojie Mao
•
Masatoshi Uehara

20191230

Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
Ruocheng Guo
•
Jundong Li
•
Huan Liu

20191222

Causal Inference and DataFusion in Econometrics
Paul Hünermund
•
Elias Bareinboim

20191219

Variablelag Granger Causality for Time Series Analysis

Chainarong Amornbunchornvej
•
Elena Zheleva
•
Tanya Y. BergerWolf

20191218

More Efficient OffPolicy Evaluation through Regularized Targeted Learning
Aurélien F. Bibaut
•
Ivana Malenica
•
Nikos Vlassis
•
Mark J. Van Der Laan

20191213

MetaCI: MetaLearning for Causal Inference in a Heterogeneous Population
Ankit Sharma
•
Garima Gupta
•
Ranjitha Prasad
•
Arnab Chatterjee
•
Lovekesh Vig
•
Gautam Shroff

20191209

Using Machine Learning to Assess Short Term Causal Dependence and Infer Network Links
Amitava Banerjee
•
Jaideep Pathak
•
Rajarshi Roy
•
Juan G. Restrepo
•
Edward Ott

20191205

Perceiving the arrow of time in autoregressive motion
Kristof Meding
•
Dominik Janzing
•
Bernhard Schölkopf
•
Felix A. Wichmann

20191201

A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits
Wenhao Zhang
•
Si Wu
•
Brent Doiron
•
Tai Sing Lee

20191201

High Dimensional MEstimation with Missing Outcomes: A SemiParametric Framework
Abhishek Chakrabortty
•
Jiarui Lu
•
T. Tony Cai
•
Hongzhe Li

20191126

Algorithmic Bias in Recidivism Prediction: A Causal Perspective
Aria Khademi
•
Vasant Honavar

20191124

Causally Denoise Word Embeddings Using HalfSibling Regression

Zekun Yang
•
Tianlin Liu

20191124

Causality for Machine Learning
Bernhard Schölkopf

20191124

RSMGAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series
Farzaneh Khoshnevisan
•
Zhewen Fan

20191116

Causal inference using Bayesian nonparametric quasiexperimental design

Max Hinne
•
Marcel A. J. van Gerven
•
Luca Ambrogioni

20191115

Causal Inference via Conditional Kolmogorov Complexity using MDL Binning
Daniel Goldfarb
•
Scott Evans

20191031

Causal inference for climate change events from satellite image time series using computer vision and deep learning
Vikas Ramachandra

20191025

Strategic Classification is Causal Modeling in Disguise
John Miller
•
Smitha Milli
•
Moritz Hardt

20191023

Doubly robust treatment effect estimation with missing attributes
Imke Mayer
•
Erik Sverdrup
•
Tobias Gauss
•
JeanDenis Moyer
•
Stefan Wager
•
Julie Josse

20191023

Leveraging directed causal discovery to detect latent common causes
Ciarán M. Lee
•
Christopher Hart
•
Jonathan G. Richens
•
Saurabh Johri

20191022

Optimising IndividualTreatmentEffect Using Bandits

Jeroen Berrevoets
•
Sam Verboven
•
Wouter Verbeke

20191016

Comment on "Blessings of Multiple Causes"
Elizabeth L. Ogburn
•
Ilya Shpitser
•
Eric J. Tchetgen Tchetgen

20191011

Kernelbased Approach to Handle Mixed Data for Inferring Causal Graphs
Teny Handhayani
•
James Cussens

20191007

Spikebased causal inference for weight alignment

Jordan Guerguiev
•
Konrad P. Kording
•
Blake A. Richards

20191003

Debiased Bayesian inference for average treatment effects

Kolyan Ray
•
Botond Szabo

20190926

Using the Prognostic Score to Reduce Heterogeneity in Observational Studies
Rachael C. Aikens
•
Dylan Greaves
•
Michael Baiocchi

20190824

Causal discovery in heavytailed models
Nicola Gnecco
•
Nicolai Meinshausen
•
Jonas Peters
•
Sebastian Engelke

20190814

Multicause causal inference with unmeasured confounding and binary outcome
Dehan Kong
•
Shu Yang
•
Linbo Wang

20190731

A neural network oracle for quantum nonlocality problems in networks

Tamás Kriváchy
•
Yu Cai
•
Daniel Cavalcanti
•
Arash Tavakoli
•
Nicolas Gisin
•
Nicolas Brunner

20190724

A discriminative approach for finding and characterizing positivity violations using decision trees
Ehud Karavani
•
Peter Bak
•
Yishai Shimoni

20190718

Quantifying Error in the Presence of Confounders for Causal Inference
Rathin Desai
•
Amit Sharma

20190710

Adjustment Criteria for Recovering Causal Effects from Missing Data
Mojdeh Saadati
•
Jin Tian

20190702

A Bayesian Solution to the MBias Problem
David Rohde

20190617

Reinforcement Knowledge Graph Reasoning for Explainable Recommendation

Yikun Xian
•
Zuohui Fu
•
S. Muthukrishnan
•
Gerard de Melo
•
Yongfeng Zhang

20190612

Learning Individual Causal Effects from Networked Observational Data

Ruocheng Guo
•
Jundong Li
•
Huan Liu

20190608

Adapting Neural Networks for the Estimation of Treatment Effects

Claudia Shi
•
David M. Blei
•
Victor Veitch

20190605

The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis
Cynthia Rudin
•
David Carlson

20190604

An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference

Yishai Shimoni
•
Ehud Karavani
•
Sivan Ravid
•
Peter Bak
•
Tan Hung Ng
•
Sharon Hensley Alford
•
Denise Meade
•
Yaara Goldschmidt

20190602

Rarelyswitching linear bandits: optimization of causal effects for the real world
Benjamin Lansdell
•
Sofia Triantafillou
•
Konrad Kording

20190530

Multiple Causes: A Causal Graphical View
Yixin Wang
•
David M. Blei

20190530

Heterogeneous causal effects with imperfect compliance: a novel Bayesian machine learning approach
Falco J. BargagliStoffi
•
Kristof DeWitte
•
Giorgio Gnecco

20190529

Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization
Yifan Hu
•
Xin Chen
•
Niao He

20190528

Contrastive Fairness in Machine Learning
Tapabrata Chakraborti
•
Arijit Patra
•
Alison Noble

20190517

An EndtoEnd Framework to Identify Pathogenic Social Media Accounts on Twitter
Elham Shaabani
•
Ashkan SadeghiMobarakeh
•
Hamidreza Alvari
•
Paulo Shakarian

20190504

Learning Information Propagation in the Dynamical Systems via Information Bottleneck Hierarchy
Gaurav Gupta
•
Mohamed Ridha Znaidi
•
Paul Bogdan

20190501

Adversarial Balancingbased Representation Learning for Causal Effect Inference with Observational Data

Xin Du
•
Lei Sun
•
Wouter Duivesteijn
•
Alexander Nikolaev
•
Mykola Pechenizkiy

20190430

A unifying approach for doublyrobust $\ell_1$ regularized estimation of causal contrasts
Ezequiel Smucler
•
Andrea Rotnitzky
•
James M. Robins

20190407

What can be estimated? Identifiability, estimability, causal inference and illposed inverse problems
Oliver J. Maclaren
•
Ruanui Nicholson

20190404

Machine Learning Methods Economists Should Know About
Susan Athey
•
Guido Imbens

20190324

Weighted Tensor Completion for TimeSeries Causal Inference

Debmalya Mandal
•
David Parkes

20190212

Using Embeddings to Correct for Unobserved Confounding in Networks

Victor Veitch
•
Yixin Wang
•
David M. Blei

20190211

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks

ChaoHan Huck Yang
•
YiChieh Liu
•
PinYu Chen
•
Xiaoli Ma
•
YiChang James Tsai

20190209

Causal Effect Identification from Multiple Incomplete Data Sources: A General Searchbased Approach

Santtu Tikka
•
Antti Hyttinen
•
Juha Karvanen

20190204

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders

Ioana Bica
•
Ahmed M. Alaa
•
Mihaela van der Schaar

20190201

Causal Discovery with a Mixture of DAGs
Eric V. Strobl

20190128

Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data
Yongjin Park
•
Abhishek Sarkar
•
Khoi Nguyen
•
Manolis Kellis

20190124

Causal mediation analysis for stochastic interventions

Iván Díaz
•
Nima Hejazi

20190109

A Bayesian Model for Bivariate Causal Inference
Maximilian Kurthen
•
Torsten A. Enßlin

20181224

Balanced Linear Contextual Bandits
Maria Dimakopoulou
•
Zhengyuan Zhou
•
Susan Athey
•
Guido Imbens

20181215

Causal inference, social networks, and chain graphs
Elizabeth L. Ogburn
•
Ilya Shpitser
•
Youjin Lee

20181212

Explainable Genetic Inheritance Pattern Prediction
Edmond Cunningham
•
Dana Schlegel
•
Andrew DeOrio

20181201

Identification and Estimation of Causal Effects from Dependent Data
Eli Sherman
•
Ilya Shpitser

20181201

Causal Inference by String Diagram Surgery
Bart Jacobs
•
Aleks Kissinger
•
Fabio Zanasi

20181120

Explaining Deep Learning Models using Causal Inference
Tanmayee Narendra
•
Anush Sankaran
•
Deepak Vijaykeerthy
•
Senthil Mani

20181111

Removing Hidden Confounding by Experimental Grounding
Nathan Kallus
•
Aahlad Manas Puli
•
Uri Shalit

20181027

Challenges of Using Text Classifiers for Causal Inference

Zach WoodDoughty
•
Ilya Shpitser
•
Mark Dredze

20181001

Early Identification of Pathogenic Social Media Accounts
Hamidreza Alvari
•
Elham Shaabani
•
Paulo Shakarian

20180925

Evaluating Fairness Metrics in the Presence of Dataset Bias
J. Henry Hinnefeld
•
Peter Cooman
•
Nat Mammo
•
Rupert Deese

20180924

Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models

Shoubo Hu
•
Zhitang Chen
•
Vahid Partovi Nia
•
Laiwan Chan
•
Yanhui Geng

20180923

Learning Optimal Fair Policies
Razieh Nabi
•
Daniel Malinsky
•
Ilya Shpitser

20180906

Understanding Perceptual and Conceptual Fluency at a Large Scale
Shengli Hu
•
Ali Borji

20180901

Transfer Learning for Estimating Causal Effects using Neural Networks
Sören R. Künzel
•
Bradly C. Stadie
•
Nikita Vemuri
•
Varsha Ramakrishnan
•
Jasjeet S. Sekhon
•
Pieter Abbeel

20180823

Discovering Context Specific Causal Relationships
Saisai Ma
•
Jiuyong Li
•
Lin Liu
•
Thuc Duy Le

20180820

Effect of secular trend in drug effectiveness study in real world data
Sharon Hensley Alford
•
Piyush Madan
•
Shilpa Mahatma
•
Italo Buleje
•
Yanyan Han
•
Fang Lu

20180818

Estimating Heterogeneous Causal Effects in the Presence of Irregular Assignment Mechanisms
Falco J. BargagliStoffi
•
Giorgio Gnecco

20180813

Local Linear Forests

Rina Friedberg
•
Julie Tibshirani
•
Susan Athey
•
Stefan Wager

20180730

CauseEffect Deep Information Bottleneck For Systematically Missing Covariates
Sonali Parbhoo
•
Mario Wieser
•
Aleksander Wieczorek
•
Volker Roth

20180706

Causal Inference for Early Detection of Pathogenic Social Media Accounts
Hamidreza Alvari
•
Paulo Shakarian

20180626

Causal Inference with Noisy and Missing Covariates via Matrix Factorization

Nathan Kallus
•
Xiaojie Mao
•
Madeleine Udell

20180603

Too Fast Causal Inference under Causal Insufficiency
Mieczysław A. Kłopotek

20180530

Counterfactual Mean Embeddings
Krikamol Muandet
•
Motonobu Kanagawa
•
Sorawit Saengkyongam
•
Sanparith Marukatat

20180522

Multiple Causal Inference with Latent Confounding
Rajesh Ranganath
•
Adler Perotte

20180521

Consistent Estimation of Propensity Score Functions with Oversampled Exposed Subjects

Sherri Rose

20180520

The Blessings of Multiple Causes

Yixin Wang
•
David M. Blei

20180517

Machine Learning for Public Administration Research, with Application to Organizational Reputation
L. Jason Anastasopoulos
•
Andrew B. Whitford

20180511

A ConstraintBased Algorithm For Causal Discovery with Cycles, Latent Variables and Selection Bias

Eric V. Strobl

20180505

Causal programming: inference with structural causal models as finding instances of a relation
Joshua Brulé

20180504

Data science is science's second chance to get causal inference right: A classification of data science tasks
Miguel A. Hernán
•
John Hsu
•
Brian Healy

20180428

Causal Inference via Kernel Deviance Measures
Jovana Mitrovic
•
Dino Sejdinovic
•
Yee Whye Teh

20180412

Merging joint distributions via causal model classes with low VC dimension
Dominik Janzing

20180409

Randomization inference with general interference and censoring
Wen Wei Loh
•
Michael G. Hudgens
•
John D. Clemens
•
Mohammad Ali
•
Michael E. Emch

20180306

Deep Learning for Causal Inference
Vikas Ramachandra

20180301

A Framework in CRM Customer Lifecycle: Identify Downward Trend and Potential Issues Detection
Kun Hu
•
Zhe Li
•
Ying Liu
•
Luyin Cheng
•
Qi Yang
•
Yan Li

20180225

Analysis of causeeffect inference by comparing regression errors
Patrick Blöbaum
•
Dominik Janzing
•
Takashi Washio
•
Shohei Shimizu
•
Bernhard Schölkopf

20180219

Benchmarking Framework for PerformanceEvaluation of Causal Inference Analysis

Yishai Shimoni
•
Chen Yanover
•
Ehud Karavani
•
Yaara Goldschmnidt

20180214

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees
AmirEmad Ghassami
•
Saber Salehkaleybar
•
Negar Kiyavash
•
Kun Zhang

20180205

Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution

Judea Pearl

20180111

Matching with Text Data: An Experimental Evaluation of Methods for Matching Documents and of Measuring Match Quality

Reagan Mozer
•
Luke Miratrix
•
Aaron Russell Kaufman
•
L. Jason Anastasopoulos

20180102

Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms
Ahmed M. Alaa
•
Mihaela van der Schaar

20171224

Permutationbased Causal Inference Algorithms with Interventions
Yuhao Wang
•
Liam Solus
•
Karren Yang
•
Caroline Uhler

20171201

Estimation Considerations in Contextual Bandits
Maria Dimakopoulou
•
Zhengyuan Zhou
•
Susan Athey
•
Guido Imbens

20171119

Causal inference for interfering units with cluster and population level treatment allocation programs
Georgia Papadogeorgou
•
Fabrizia Mealli
•
Corwin M. Zigler

20171103

SynthValidation: Selecting the Best Causal Inference Method for a Given Dataset
Alejandro Schuler
•
Ken Jung
•
Robert Tibshirani
•
Trevor Hastie
•
Nigam Shah

20171031

A Framework for Inferring Causality from MultiRelational Observational Data using Conditional Independence
Sudeepa Roy
•
Babak Salimi

20170808

Uncertainty Assessment and False Discovery Rate Control in HighDimensional Granger Causal Inference
Aditya Chaudhry
•
Pan Xu
•
Quanquan Gu

20170801

Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Sara Magliacane
•
Thijs van Ommen
•
Tom Claassen
•
Stephan Bongers
•
Philip Versteeg
•
Joris M. Mooij

20170720

FLAME: A Fast Largescale Almost Matching Exactly Approach to Causal Inference
Tianyu Wang
•
Marco Morucci
•
M. Usaid Awan
•
Yameng Liu
•
Sudeepa Roy
•
Cynthia Rudin
•
Alexander Volfovsky

20170719

Automated versus doityourself methods for causal inference: Lessons learned from a data analysis competition
Vincent Dorie
•
Jennifer Hill
•
Uri Shalit
•
Marc Scott
•
Dan Cervone

20170709

Collaborativecontrolled LASSO for Constructing Propensity Scorebased Estimators in HighDimensional Data
Cheng Ju
•
Richard Wyss
•
Jessica M. Franklin
•
Sebastian Schneeweiss
•
Jenny Häggström
•
Mark J. Van Der Laan

20170630

Deep Counterfactual Networks with PropensityDropout

Ahmed M. Alaa
•
Michael Weisz
•
Mihaela van der Schaar

20170619

Bias and highdimensional adjustment in observational studies of peer effects

Dean Eckles
•
Eytan Bakshy

20170614

Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami
•
Saber Salehkaleybar
•
Negar Kiyavash
•
Kun Zhang

20170526

Causal inference for social network data
Elizabeth L. Ogburn
•
Oleg Sofrygin
•
Ivan Diaz
•
Mark J. Van Der Laan

20170523

Causal Inference through the Method of Direct Estimation
Marc Ratkovic
•
Dustin Tingley

20170316

Probabilistic Matching: Causal Inference under Measurement Errors
Fani Tsapeli
•
Peter Tino
•
Mirco Musolesi

20170313

Causal Inference by Stochastic Complexity
Kailash Budhathoki
•
Jilles Vreeken

20170222

A Bayesian view of doubly robust causal inference

Olli Saarela
•
Léo R. Belzile
•
David A. Stephens

20170115

Generalized Optimal Matching Methods for Causal Inference
Nathan Kallus

20161226

Joint Causal Inference from Multiple Contexts
Joris M. Mooij
•
Sara Magliacane
•
Tom Claassen

20161130

Entropic Causal Inference

Murat Kocaoglu
•
Alexandros G. Dimakis
•
Sriram Vishwanath
•
Babak Hassibi

20161112

Sensitivity Maps of the HilbertSchmidt Independence Criterion
Adrián PérezSuay
•
Gustau CampsValls

20161102

ZaliQL: A SQLBased Framework for Drawing Causal Inference from Big Data
Babak Salimi
•
Dan Suciu

20160912

The Inflation Technique for Causal Inference with Latent Variables
Elie Wolfe
•
Robert W. Spekkens
•
Tobias Fritz

20160902

Identifying Candidate Risk Factors for Prescription Drug Side Effects using Causal Contrast Set Mining
Jenna Reps
•
Zhaoyang Guo
•
Haoyue Zhu
•
Uwe Aickelin

20160720

From Dependence to Causation
David LopezPaz

20160712

Estimating individual treatment effect: generalization bounds and algorithms

Uri Shalit
•
Fredrik D. Johansson
•
David Sontag

20160613

The Crossover Process: Learnability and Data Protection from Inference Attacks
Richard Nock
•
Giorgio Patrini
•
Finnian Lattimore
•
Tiberio Caetano

20160613

Causal Bandits: Learning Good Interventions via Causal Inference
Finnian Lattimore
•
Tor Lattimore
•
Mark D. Reid

20160610

Learning Representations for Counterfactual Inference

Fredrik D. Johansson
•
Uri Shalit
•
David Sontag

20160512

Private Causal Inference
Matt J. Kusner
•
Yu Sun
•
Karthik Sridharan
•
Kilian Q. Weinberger

20151217

Causal and anticausal learning in pattern recognition for neuroimaging
Sebastian Weichwald
•
Bernhard Schölkopf
•
Tonio Ball
•
Moritz GrosseWentrup

20151215

Causal Model Analysis using Collider vstructure with Negative Percentage Mapping
Pramod Kumar Parida
•
Tshilidzi Marwala
•
Snehashish Chakraverty

20150916

Samplingbased Causal Inference in Cue Combination and its Neural Implementation
Zhaofei Yu
•
Feng Chen
•
Jianwu Dong
•
Qionghai Dai

20150903

Causal Decision Trees
Jiuyong Li
•
Saisai Ma
•
Thuc Duy Le
•
Lin Liu
•
Jixue Liu

20150816

Learning from Pairwise Marginal Independencies
Johannes Textor
•
Alexander Idelberger
•
Maciej Liśkiewicz

20150802

Removing systematic errors for exoplanet search via latent causes

Bernhard Schölkopf
•
David W. Hogg
•
Dun Wang
•
Daniel ForemanMackey
•
Dominik Janzing
•
CarlJohann SimonGabriel
•
Jonas Peters

20150512

Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales
•
Dominik Janzing
•
Bernhard Shoelkopf
•
Michel Besserve

20150304

A fast PC algorithm for high dimensional causal discovery with multicore PCs

Thuc Duy Le
•
Tao Hoang
•
Jiuyong Li
•
Lin Liu
•
Huawen Liu

20150209

Towards a Learning Theory of CauseEffect Inference

David LopezPaz
•
Krikamol Muandet
•
Bernhard Schölkopf
•
Ilya Tolstikhin

20150209

Distinguishing cause from effect using observational data: methods and benchmarks
Joris M. Mooij
•
Jonas Peters
•
Dominik Janzing
•
Jakob Zscheischler
•
Bernhard Schölkopf

20141211

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components
Philipp Geiger
•
Kun Zhang
•
Mingming Gong
•
Dominik Janzing
•
Bernhard Schölkopf

20141114

Nonlinear Causal Inference using Gaussianity Measures
Daniel HernándezLobato
•
Pablo MoralesMombiela
•
David LopezPaz
•
Alberto Suárez

20140916

The Randomized Causation Coefficient
David LopezPaz
•
Krikamol Muandet
•
Benjamin Recht

20140915

Attributes for Causal Inference in Longitudinal Observational Databases
Jenna Reps
•
Jonathan M. Garibaldi
•
Uwe Aickelin
•
Daniele Soria
•
Jack E. Gibson
•
Richard B. Hubbard

20140903

Inferring causal structure: a quantum advantage
Katja Ried
•
Megan Agnew
•
Lydia Vermeyden
•
Dominik Janzing
•
Robert W. Spekkens
•
Kevin J. Resch

20140619

Causal Inference through a Witness Protection Program
Ricardo Silva
•
Robin Evans

20140602

Counterfactual Estimation and Optimization of Click Metrics for Search Engines
Lihong Li
•
Shunbao Chen
•
Jim Kleban
•
Ankur Gupta

20140307

Justifying InformationGeometric Causal Inference
Dominik Janzing
•
Bastian Steudel
•
Naji Shajarisales
•
Bernhard Schölkopf

20140211

Consistency of Causal Inference under the Additive Noise Model
Samory Kpotufe
•
Eleni Sgouritsa
•
Dominik Janzing
•
Bernhard Schölkopf

20131219

Feedback Detection for Live Predictors
Stefan Wager
•
Nick Chamandy
•
Omkar Muralidharan
•
Amir Najmi

20131010

On the definition of a confounder
Tyler J. VanderWeele
•
Ilya Shpitser

20130402

Counterfactual Reasoning and Learning Systems
Léon Bottou
•
Jonas Peters
•
Joaquin QuiñoneroCandela
•
Denis X. Charles
•
D. Max Chickering
•
Elon Portugaly
•
Dipankar Ray
•
Patrice Simard
•
Ed Snelson

20120911

Quantifying causal influences
Dominik Janzing
•
David Balduzzi
•
Moritz GrosseWentrup
•
Bernhard Schölkopf

20120329
