UAI 2019 - Program Schedule

Videos of Tutorials, Invited Talks and Plenary presentations are available on the UAI 2019 YouTube Channel

July 22nd: Tutorials

Time Event
8:00am - 6:00pm Registration
8:30am - 10:30am Tutorial 1: Tractable Probabilistic Models: Representations, Algorithms, Learning, and Applications
10:30am - 12:30pm Tutorial 2: Mixing Graphical Models and Neural Nets Like Chocolate and Peanut Butter
12:30pm - 2:00pmLunch break (on your own)
2:00pm - 4:00pm Tutorial 3: Causal Reinforcement Learning
4:00pm - 6:00pm Tutorial 4: Mathematics of Deep Learning

July 23rd: Main Conference

Time Event
7:50am - 6:30pmRegistration
8:40am - 9:00amOpening remarks
9:00am - 10:00amInvited talk: Rina Dechter
10:00am - 10:20amCoffee break
10:20am - 12:00pmOral session:
10:20 ID: 264 (pdf) | Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation | Théo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper
10:40 ID: 356 (pdf) | Generating and Sampling Orbits for Lifted Probabilistic Inference | Steven Holtzen, Todd Millstein, Guy Van den Broeck
11:00 ID: 6 (pdf) | Conditional Expectation Propagation | Zheng Wang, Shandian Zhe
11:20 ID: 221 (pdf) | Belief Propagation: Accurate Marginals or Accurate Partition Function -- Where is the Difference? | Christian Knoll, Franz Pernkopf
11:40 ID: 204 (pdf) | Sliced Score Matching: A Scalable Approach to Density and Score Estimation | Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon
12:00pm - 2:00pmLunch break (on your own)
2:00pm - 2:30pmSpotlight session 1
2:30pm - 2:50pmOral session:
2:30 ID: 124 (pdf) | Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning | Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
2:50pm - 3:20pmSpotlight session 2
3:20pm - 3:40pmCoffee break
3:40pm - 5:20pmOral session:
3:40 ID: 91 (pdf) | Towards a Better Understanding and Regularization of GAN Training Dynamics | Weili Nie, Ankit Patel
4:00 ID: 159 (pdf) | Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks | Qi She, Anqi Wu
4:20 ID: 164 (pdf) | Efficient Neural Network Verification with Exactness Characterization | Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli
4:40 ID: 253 (pdf) | Sinkhorn AutoEncoders | Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen
5:00 ID: 244 (pdf) | Learning with Non-Convex Truncated Losses by SGD | Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang
5:20pm - 6:20pmInvited talk: Suchi Saria
6:20pm - 9:00pmPoster session

July 24th: Main Conference

Time Event
8:00am - 3:30pmRegistration
8:40am - 9:40amInvited talk: Stefanie Jegelka
9:40am - 10:00amOral session:
9:40 ID: 144 (pdf) | General Identifiability with Arbitrary Surrogate Experiments | Sanghack Lee, Juan D. Correa, Elias Bareinboim
10:00am - 10:20amCoffee break
10:20am - 12:00pmOral session:
10:20 ID: 481 (pdf) | On Open-Universe Causal Reasoning | Duligur Ibeling, Thomas Icard
10:40 ID: 210 (pdf) | Approximate Causal Abstractions | Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern
11:00 ID: 205 (pdf) | Beyond Structural Causal Models: Causal Constraints Models | Tineke Blom, Stephan Bongers, Joris M. Mooij
11:20 ID: 512 (pdf) | Exclusivity Graph Approach to Instrumental Inequalities | Davide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino
11:40 ID: 222 (pdf) | Finding Minimal d-separators in Linear Time and Applications | Benito van der Zander, Maciej Liśkiewicz
12:00pm - 1:30pmLight lunch will be served in the hotel (Azure room)
1:30pm - 2:30pmInvited talk: Emma Brunskill
2:30pm - 3:10pmOral session:
2:30 ID: 440 (pdf) | Off-Policy Policy Gradient with Stationary Distribution Correction | Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2:50 ID: 315 (pdf) | Wasserstein Fair Classification | Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
3:20pm - 3:40pmCoffee break
3:40pm - 4:00pmOral session:
3:40 ID: 158 (pdf) | A Fast Proximal Point Method for Computing Exact Wasserstein Distance | Yujia Xie, Xiangfeng Wang, Ruijia Wang, Hongyuan Zha
4:00pm - 4:30pmAUAI Business Meeting
4:30pm - 11:00pmBanquet in Jerusalem

July 25th: Main Conference

Time Event
8:00am - 12:00pmRegistration
8:40am - 9:40amInvited talk: Yee Whey Teh
9:40am - 10:00amOral session:
9:40 ID: 345 (pdf) | Exact Sampling of Directed Acyclic Graphs from Modular Distributions | Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto
10:00am - 10:20amCoffee break
10:20am - 12:00pmOral session:
10:20 ID: 468 (pdf) | Bayesian Optimization with Binary Auxiliary Information | Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low
10:40 ID: 176 (pdf) | Perturbed-History Exploration in Stochastic Linear Bandits | Branislav Kveton, Csaba Szepesvari, Mohammad Ghavamzadeh, Craig Boutilier
11:00 ID: 248 (pdf) | Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank | Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton
11:20 ID: 267 (pdf) | A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations | Biswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos
11:40 ID: 407 (pdf) | On the Relationship Between Satisfiability and Markov Decision Processes | Ricardo Salmon, Pascal Poupart
12:00pm - 1:30pmLunch break (on your own)
1:30pm - 2:50pmOral session:
1:30 ID: 228 (pdf) | A Bayesian Approach to Robust Reinforcement Learning | Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
1:50 ID: 191 (pdf) | An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient | Pan Xu, Felicia Gao, Quanquan Gu
2:10 ID: 441 (pdf) | Co-training for Policy Learning | Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono
2:30 ID: 21 (pdf) | Truly Proximal Policy Optimization | Yuhui Wang, Hao He, Xiaoyang Tan
2:50pm - 3:20pmSpotlight session 1
3:20pm - 3:40pmCoffee break
3:40pm - 5:20pmOral session:
3:40 ID: 14 (pdf) | Correlated Learning for Aggregation Systems | Tanvi Verma, Pradeep Varakantham
4:00 ID: 49 (pdf) | Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory | Philipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schoelkopf
4:20 ID: 335 (pdf) | Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning | Smitha Milli, Anca D. Dragan
4:40 ID: 64 (pdf) | Randomized Iterative Algorithms for Fisher Discriminant Analysis | Agniva Chowdhury, Jiasen Yang, Petros Drineas
5:00 ID: 28 (pdf) | Countdown Regression: Sharp and Calibrated Survival Predictions | Anand Avati, Tony Duan, Sharon Zhou, Ken Jung, Nigam H. Shah, Andrew Ng
5:20pm - 5:50pmSpotlight session 2
6:15pm - 9:00pmPoster session

Spotlight and Poster Session - July 23rd - Tuesday

Spotlight 1 (Tue 2:50pm - 3:20pm) & Poster (Tue 6:15pm - 9:00pm)

ID: 275 (pdf) | Efficient Multitask Feature and Relationship Learning
Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
ID: 174 (pdf) | A Tighter Analysis of Randomised Policy Iteration
Meet Taraviya, Shivaram Kalyanakrishnan
ID: 427 (pdf) | Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption
Ondrej Kuzelka, Jesse Davis
ID: 340 (pdf) | End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations
Gregory Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt
ID: 290 (pdf) | Adaptively Truncating Backpropagation Through Time to Control Gradient Bias
Christopher Aicher, Nicholas J. Foti, Emily B. Fox
ID: 380 (pdf) | Learnability for the Information Bottleneck
Tailin Wu, Ian Fischer, Isaac Chuang, Max Tegmark
ID: 35 (pdf) | Efficient Search-Based Weighted Model Integration
Zhe Zeng, Guy Van den Broeck
ID: 15 (pdf) | Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
Patrick Forré, Joris M. Mooij
ID: 324 (pdf) | On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits
Roman Pogodin, Tor Lattimore
ID: 193 (pdf) | Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haußmann, Fred A. Hamprecht, Melih Kandemir
ID: 372 (pdf) | Causal Inference Under Interference and Network Uncertainty
Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser
ID: 235 (pdf) | Probabilistic Programming for Birth-Death Models of Evolution using an Alive Particle Filter with Delayed Sampling
Jan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön
ID: 213 (pdf) | The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva
ID: 24 (pdf) | Learning Factored Markov Decision Processes with Unawareness
Craig Innes, Alex Lascarides
ID: 296 (pdf) | Sampling-Free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging
Seong Jae Hwang, Ronak R. Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh
ID: 17 (pdf) | Recommendation from Raw Data with Adaptive Compound Poisson Factorization
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
ID: 148 (pdf) | Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem
Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David Fleet, Max Welling
ID: 1 (pdf) | Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data
Naman Goel, Boi Faltings
ID: 19 (pdf) | One-Shot Inference in Markov Random Fields
Hao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi
ID: 403 (pdf) | CCMI : Classifier based Conditional Mutual Information Estimation
Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan
ID: 245 (pdf) | Active Multi-Information Source Bayesian Quadrature
Alexandra Gessner, Javier Gonzalez, Maren Mahsereci
ID: 129 (pdf) | Random Search and Reproducibility for Neural Architecture Search
Liam Li, Ameet Talwalkar

Spotlight 2 (Tue 5:20pm - 5:50pm) & Poster (Tue 6:15pm - 9:00pm)

ID: 435 (pdf) | Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon Wilson
ID: 33 (pdf) | Comparing EM with GD in Mixture Models of Two Components
Guojun Zhang, Pascal Poupart, George Trimponias
ID: 25 (pdf) | Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely
ID: 352 (pdf) | Intervening on Network Ties
Eli Sherman, Ilya Shpitser
ID: 162 (pdf) | Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning
Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee
ID: 53 (pdf) | The Incomplete Rosetta Stone problem: Identifiability Results for Multi-View Nonlinear ICA
Luigi Gresele, Paul Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schoelkopf
ID: 101 (pdf) | Domain Generalization via Multidomain Discriminant Analysis
Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan
ID: 55 (pdf) | Random Clique Covers for Graphs with Local Density and Global Sparsity
Sinead A. Williamson, Mauricio Tec
ID: 45 (pdf) | Causal Discovery with General Non-Linear Relationships using Non-Linear ICA
Ricardo Pio Monti, Kun Zhang, Aapo Hyvarinen
ID: 172 (pdf) | Augmenting and Tuning Knowledge Graph Embeddings
Robert Bamler, Farnood Salehi, Stephan Mandt
ID: 156 (pdf) | Randomized Value Functions via Multiplicative Normalizing Flows
Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent
ID: 319 (pdf) | Guaranteed Scalable Learning of Latent Tree Models
Furong Huang, Niranjan UN, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar
ID: 127 (pdf) | Towards Robust Relational Causal Discovery
Sanghack Lee, Vasant Honavar
ID: 443 (pdf) | Variational Inference of Penalized Regression with Submodular Functions
Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara
ID: 496 (pdf) | Embarrassingly Parallel MCMC using Deep Invertible Transformations
Diego Mesquita, Paul Blomstedt, Samuel Kaski
ID: 511 (pdf) | Block Neural Autoregressive Flow
Nicola De Cao, Wilker Aziz, Ivan Titov
ID: 508 (pdf) | Fast Proximal Gradient Descent for A Class of Non-convex and Non-smooth Sparse Learning Problems
Yingzhen Yang, Jiahui Yu
ID: 410 (pdf) | Interpretable Almost Matching Exactly With Instrumental Variables
M.Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
ID: 7 (pdf) | A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels
Martin Slawski, Mostafa Rahmani, Ping Li
ID: 332 (pdf) | Noise Contrastive Priors for Functional Uncertainty
Danijar Hafner, Dustin Tran, Timothy Lillicrap, Alex Irpan, James Davidson
ID: 411 (pdf) | Low Frequency Adversarial Perturbation
Chuan Guo, Jared S. Frank, Kilian Q. Weinberger
ID: 383 (pdf) | Learning Belief Representations for Imitation Learning in POMDPs
Tanmay Gangwani, Joel Lehman, Qiang Liu, Jian Peng

Banquet in Jerusalem - July 24th - Wednesday

  • The banquet will be held in the Tower of David Museum of the History of Jerusalem (please note, the exhibits will be closed).
  • There will be six buses taking attendees from the hotel at 4:40pm. Buses back will be spread out between 10pm and 10:30pm.
  • Dinner will be served there starting 7pm. Then there will be an audio-visual show around 8:30pm.

Spotlight and Poster Session - July 25th - Thursday

Spotlight 1 (Thu 2:50pm - 3:20pm) & Poster (Thu 6:15pm - 9:00pm)

ID: 312 (pdf) | Problem-dependent Regret Bounds for Online Learning with Feedback Graphs
Bingshan Hu, Nishant A. Mehta, Jianping Pan
ID: 317 (pdf) | Variational Training for Large-Scale Noisy-OR Bayesian Networks
Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik Sudderth
ID: 32 (pdf) | Reducing Exploration of Dying Arms in Mortal Bandits
Stefano Tracà, Weiyu Yan, Cynthia Rudin
ID: 239 (pdf) | Variational Sparse Coding
Francesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith
ID: 86 (pdf) | Adaptive Hashing for Model Counting
Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon
ID: 152 (pdf) | Approximate Inference in Structured Instances with Noisy Categorical Observations
Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas
ID: 47 (pdf) | BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback
Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvari, Masrour Zoghi
ID: 13 (pdf) | On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function
Xingguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
ID: 78 (pdf) | Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests
Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang
ID: 192 (pdf) | Deep Mixture of Experts via Shallow Embedding
Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez
ID: 371 (pdf) | P3O: Policy-on Policy-off Policy Optimization
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
ID: 262 (pdf) | How to Exploit Structure while Solving Weighted Model Integration Problems
Samuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt
ID: 122 (pdf) | Stability of Linear Structural Equation Models of Causal Inference
Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
ID: 339 (pdf) | Convergence Analysis of Gradient-Based Learning in Continuous Games
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Sam Burden
ID: 310 (pdf) | N-GCN: Multi-scale Graph Convolution for Semi-Supervised Node Classification
Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee
ID: 284 (pdf) | Practical Multi-Fidelity Bayesian Optimization for Hyperparameter Tuning
Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson
ID: 118 (pdf) | Cubic Regularization with Momentum for Nonconvex Optimization
Zhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan
ID: 112 (pdf) | Efficient Planning Under Uncertainty with Incremental Refinement
Juan Carlos Saborío, Joachim Hertzberg
ID: 368 (pdf) | Real-Time Robotic Search using Structural Spatial Point Processes
Olov Andersson, Per Sidén, Johan Dahlin, Patrick Doherty, Mattias Villani
ID: 83 (pdf) | Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta

Spotlight 2 (Thu 5:20pm - 5:50pm) & Poster (Thu 6:15pm - 9:00pm)

ID: 161 (pdf) | Fisher-Bures Adversary Graph Convolutional Networks
Ke Sun, Piotr Koniusz, Zhen Wang
ID: 138 (pdf) | Joint Nonparametric Precision Matrix Estimation with Confounding
Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
ID: 373 (pdf) | Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood
ID: 234 (pdf) | Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones
Adithya Raam Sankar, Prashant Doshi, Adam Goodie
ID: 206 (pdf) | Be Greedy: How Chromatic Number meets Regret Minimization in Graph Bandits
Aadirupa Saha, Shreyas Sheshadri, Chiranjib Bhattacharyya
ID: 370 (pdf) | Social Reinforcement Learning to Combat Fake News Spread
Mahak Goindani, Jennifer Neville
ID: 302 (pdf) | On Densification for Minwise Hashing
Tung Mai, Anup Rao, Matt Kapilevich, Ryan Rossi, Yasin Abbsi Yadkori, Ritwik Sinha
ID: 128 (pdf) | The Role of Memory in Stochastic Optimization
Antonio Orvieto, Jonas Kohler, Aurelien Lucchi
ID: 163 (pdf) | Periodic Kernel Approximation by Index Set Fourier Series Features
Anthony Tompkins, Fabio Ramos
ID: 334 (pdf) | Fake It Till You Make It: Learning-Compatible Performance Support
Jonathan Bragg, Emma Brunskill
ID: 232 (pdf) | Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Lijun Zhang
ID: 299 (pdf) | Online Factorization and Partition of Complex Networks by Random Walk
Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang
ID: 406 (pdf) | Empirical Mechanism Design: Designing Mechanisms from Data
Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald
ID: 428 (pdf) | Identification In Missing Data Models Represented By Directed Acyclic Graphs
Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins
ID: 450 (pdf) | Probability Distillation: A Caveat and Alternatives
Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville
ID: 16 (pdf) | Variational Regret Bounds for Reinforcement Learning
Ronald Ortner, Pratik Gajane, Peter Auer
ID: 341 (pdf) | Approximate Relative Value Learning for Average-Reward Continuous state MDPs
Hiteshi Sharma, Mehdi Jafarnia-Jahromi, Rahul Jain
ID: 432 (pdf) | A Weighted Mini-Bucket Bound for Solving Influence Diagram
Junkyu Lee, Radu Marinescu, Alexander Iher, Rina Dechter
ID: 393 (pdf) | Object Conditioning for Causal Inference
David Jensen, Javier Burroni, Matthew Rattigan

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