Project Causica:

Project Causica: Decision Optimization with Causal ML

Publications

Key publications:

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez Lobato (opens in new tab), Sebastian Nowozin, Cheng Zhang
International Conference on Machine Learning | June 2019
View Publication (opens in new tab)

Deep End-to-end Causal Inference

Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
View Publication (opens in new tab)

Other Publications:

View by:

- Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
  
  Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
  
  ICLR 2023 | May 2023
  
  Publication
- A Causal AI Suite for Decision-Making
  
  Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
  
  Publication Project Project
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
  
  Publication Project
- Optimal Transport for Causal Discovery
  
  Ruibo Tu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang
  
  ICLR 2022 | April 2022
  
  Publication
- Simultaneous Missing Value Imputation and Structure Learning with Groups
  
  Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  2022 Neural Information Processing Systems | February 2022
  
  Publication Publication
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2022-1 | February 2022
  
  Published by Microsoft
  
  Publication Project
- Local Constraint-Based Causal Discovery under Selection Bias
  
  Philip Versteeg, Cheng Zhang, Joris Mooij
  
  Conference on Causal Learning and Reasoning (CLeaR) | January 2022
  
  Publication
- Identifiable Generative Models for Missing Not at Random Data Imputation
  
  Chao Ma, Cheng Zhang
  
  NeurIPS | December 2021
  
  Publication
- Sparse Uncertainty Representation in Deep Learning with Inducing Weights
  
  Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li
  
  NeurIPS | December 2021
  
  Publication
- DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
  
  Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
  
  MSR-TR-2021-15 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication Project
- Optimal transport for causal discovery
  
  Ruibo Tu, Kun Zhang, Hedvig Kjellstrom, Cheng Zhang
  
  | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Probabilistic DAG Search
  
  Julia Grosse, Cheng Zhang, Philipp Hennig
  
  Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
  
  Publication
- VICAUSE: Simultaneous missing value imputation and causal discovery
  
  Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2021-14 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Meta-Learning for Variational Inference
  
  Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
  
  International Conference on Artificial Intelligence and Statistics | April 2021
  
  PDF Publication Publication Publication Publication
- Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Yordan Zaykov, Pashmina Cameron, Jose Miguel Hernandez-Lobato, Richard E. Turner, Richard G. Baraniuk, Simon Peyton Jones, Craig Barton, Simon Woodhead, Cheng Zhang
  
  NeurIPS Competition | April 2021
  
  To appear in PMLR proceeding of NeurIPS competition
  
  Preprint
- Educational Question Mining At Scale: Prediction, Analysis and Personalization
  
  Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Jones Simon Peyton, Richard G. Baraniuk, Cheng Zhang
  
  Symposium on Educational Advances in Artificial Intelligence (AAAI-EAAI) | February 2021
  
  Publication Publication
- Estimating α-Rank by Maximizing Information Gain.
  
  Tabish Rashid, Cheng Zhang, Kamil Ciosek
  
  AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
  
  Publication Project
- VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
  
  Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF Publication Publication Publication Publication
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Kun Zhang, Yingzhen Li
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF PDF Publication Publication Publication Publication Publication Publication Publication Publication
- Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, Jose Miguel Hernandez Lobato, Richard Turner, Richard Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
  
  July 2020
  
  Publication
- Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
  
  David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
  
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Project
- Advances in Variational Inference
  
  Cheng Zhang, Judith Butepage, Hedvig Kjellstrom, Stephan Mandt
  
  IEEE Transactions on Pattern Analysis and Machine Intelligence | August 2019, Vol 41(8): pp. 2008-2026
  
  Publication
- EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
  
  Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez Lobato, Sebastian Nowozin, Cheng Zhang
  
  International Conference on Machine Learning | June 2019
  
  Publication
- Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
  
  Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
  
  arXiv:1906.00429 | June 2019
  
  Published by arXiv
  
  Publication Project
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Yingzhen Li
  
  June 2019
  
  Publication
- Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
  
  Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellström, Cheng Zhang
  
  June 2019
  
  Publication
- Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
  
  Anna-Lena Popkes, Hiske Overweg, Ari Ercole, Yingzhen Li, Jose Miguel Hern´andez-Lobato, Yordan Zaykov, Cheng Zhang
  
  May 2019
  
  Publication Github
- Causal Discovery in the Presence of Missing Data
  
  Cheng Zhang, Ruibo Tu, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang
  
  International Conference on Artificial Intelligence and Statistics (AISTATS) | April 2019
  
  Editor(s): Kamalika Chaudhuri, Masashi Sugiyama
  
  Publication

- Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
  
  Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
  
  ICLR 2023 | May 2023
  
  Publication
- A Causal AI Suite for Decision-Making
  
  Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
  
  Publication Project Project
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
  
  Publication Project
- Optimal Transport for Causal Discovery
  
  Ruibo Tu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang
  
  ICLR 2022 | April 2022
  
  Publication
- Simultaneous Missing Value Imputation and Structure Learning with Groups
  
  Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  2022 Neural Information Processing Systems | February 2022
  
  Publication Publication
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2022-1 | February 2022
  
  Published by Microsoft
  
  Publication Project
- Local Constraint-Based Causal Discovery under Selection Bias
  
  Philip Versteeg, Cheng Zhang, Joris Mooij
  
  Conference on Causal Learning and Reasoning (CLeaR) | January 2022
  
  Publication
- Sparse Uncertainty Representation in Deep Learning with Inducing Weights
  
  Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li
  
  NeurIPS | December 2021
  
  Publication
- Identifiable Generative Models for Missing Not at Random Data Imputation
  
  Chao Ma, Cheng Zhang
  
  NeurIPS | December 2021
  
  Publication
- DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
  
  Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
  
  MSR-TR-2021-15 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication Project
- VICAUSE: Simultaneous missing value imputation and causal discovery
  
  Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2021-14 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Optimal transport for causal discovery
  
  Ruibo Tu, Kun Zhang, Hedvig Kjellstrom, Cheng Zhang
  
  | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Probabilistic DAG Search
  
  Julia Grosse, Cheng Zhang, Philipp Hennig
  
  Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
  
  Publication
- Meta-Learning for Variational Inference
  
  Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
  
  International Conference on Artificial Intelligence and Statistics | April 2021
  
  PDF Publication Publication Publication Publication
- Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Yordan Zaykov, Pashmina Cameron, Jose Miguel Hernandez-Lobato, Richard E. Turner, Richard G. Baraniuk, Simon Peyton Jones, Craig Barton, Simon Woodhead, Cheng Zhang
  
  NeurIPS Competition | April 2021
  
  To appear in PMLR proceeding of NeurIPS competition
  
  Preprint
- Educational Question Mining At Scale: Prediction, Analysis and Personalization
  
  Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Jones Simon Peyton, Richard G. Baraniuk, Cheng Zhang
  
  Symposium on Educational Advances in Artificial Intelligence (AAAI-EAAI) | February 2021
  
  Publication Publication
- Estimating α-Rank by Maximizing Information Gain.
  
  Tabish Rashid, Cheng Zhang, Kamil Ciosek
  
  AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
  
  Publication Project
- VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
  
  Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF Publication Publication Publication Publication
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Kun Zhang, Yingzhen Li
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF PDF Publication Publication Publication Publication Publication Publication Publication Publication
- Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, Jose Miguel Hernandez Lobato, Richard Turner, Richard Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
  
  July 2020
  
  Publication
- Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
  
  David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
  
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Project
- Advances in Variational Inference
  
  Cheng Zhang, Judith Butepage, Hedvig Kjellstrom, Stephan Mandt
  
  IEEE Transactions on Pattern Analysis and Machine Intelligence | August 2019, Vol 41(8): pp. 2008-2026
  
  Publication
- EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
  
  Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez Lobato, Sebastian Nowozin, Cheng Zhang
  
  International Conference on Machine Learning | June 2019
  
  Publication
- Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
  
  Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
  
  arXiv:1906.00429 | June 2019
  
  Published by arXiv
  
  Publication Project
- Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
  
  Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellström, Cheng Zhang
  
  June 2019
  
  Publication
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Yingzhen Li
  
  June 2019
  
  Publication
- Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
  
  Anna-Lena Popkes, Hiske Overweg, Ari Ercole, Yingzhen Li, Jose Miguel Hern´andez-Lobato, Yordan Zaykov, Cheng Zhang
  
  May 2019
  
  Publication Github
- Causal Discovery in the Presence of Missing Data
  
  Cheng Zhang, Ruibo Tu, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang
  
  International Conference on Artificial Intelligence and Statistics (AISTATS) | April 2019
  
  Editor(s): Kamalika Chaudhuri, Masashi Sugiyama
  
  Publication
- Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
  
  Anna-Lena Popkes, Hiske Overweg, Ari Ercole, Yingzhen Li, Jose Miguel Hern´andez-Lobato, Yordan Zaykov, Cheng Zhang
  
  May 2019
  
  Publication Github

- Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning
  
  Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
  
  ICLR 2023 | May 2023
  
  Publication
- A Causal AI Suite for Decision-Making
  
  Emre Kiciman, Eleanor Dillon, Darren Edge, Adam Foster, Agrin Hilmkil, Joel Jennings, Chao Ma, Robert Osazuwa Ness, Nick Pawlowski, Amit Sharma, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causality for Real-world Impact | December 2022
  
  Publication Project Project
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Agrin Hilmkil, Joel Jennings, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
  
  NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022) | November 2022
  
  Publication Project
- Optimal Transport for Causal Discovery
  
  Ruibo Tu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang
  
  ICLR 2022 | April 2022
  
  Publication
- Simultaneous Missing Value Imputation and Structure Learning with Groups
  
  Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  2022 Neural Information Processing Systems | February 2022
  
  Publication Publication
- Local Constraint-Based Causal Discovery under Selection Bias
  
  Philip Versteeg, Cheng Zhang, Joris Mooij
  
  Conference on Causal Learning and Reasoning (CLeaR) | January 2022
  
  Publication
- Sparse Uncertainty Representation in Deep Learning with Inducing Weights
  
  Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li
  
  NeurIPS | December 2021
  
  Publication
- Identifiable Generative Models for Missing Not at Random Data Imputation
  
  Chao Ma, Cheng Zhang
  
  NeurIPS | December 2021
  
  Publication
- Probabilistic DAG Search
  
  Julia Grosse, Cheng Zhang, Philipp Hennig
  
  Conference on Uncertainty in Artificial Intelligence (UAI) 2021 | July 2021
  
  Publication
- Meta-Learning for Variational Inference
  
  Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
  
  International Conference on Artificial Intelligence and Statistics | April 2021
  
  PDF Publication Publication Publication Publication
- Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Yordan Zaykov, Pashmina Cameron, Jose Miguel Hernandez-Lobato, Richard E. Turner, Richard G. Baraniuk, Simon Peyton Jones, Craig Barton, Simon Woodhead, Cheng Zhang
  
  NeurIPS Competition | April 2021
  
  To appear in PMLR proceeding of NeurIPS competition
  
  Preprint
- Educational Question Mining At Scale: Prediction, Analysis and Personalization
  
  Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Jones Simon Peyton, Richard G. Baraniuk, Cheng Zhang
  
  Symposium on Educational Advances in Artificial Intelligence (AAAI-EAAI) | February 2021
  
  Publication Publication
- Estimating α-Rank by Maximizing Information Gain.
  
  Tabish Rashid, Cheng Zhang, Kamil Ciosek
  
  AAAI Conference on Artificial Intelligence (AAAI 2021) | January 2021
  
  Publication Project
- VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
  
  Chao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF Publication Publication Publication Publication
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Kun Zhang, Yingzhen Li
  
  2020 Neural Information Processing Systems | December 2020
  
  PDF PDF PDF Publication Publication Publication Publication Publication Publication Publication Publication
- Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
  
  David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, Jose Miguel Hernandez Lobato, Sebastian Tschiatschek
  
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS) | December 2019
  
  Project
- EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
  
  Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Miguel Hernandez Lobato, Sebastian Nowozin, Cheng Zhang
  
  International Conference on Machine Learning | June 2019
  
  Publication
- Causal Discovery in the Presence of Missing Data
  
  Cheng Zhang, Ruibo Tu, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang
  
  International Conference on Artificial Intelligence and Statistics (AISTATS) | April 2019
  
  Editor(s): Kamalika Chaudhuri, Masashi Sugiyama
  
  Publication
- Deep End-to-end Causal Inference
  
  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman (emrek), Amit Sharma, Martin Kukla, Nick Pawlowski, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2022-1 | February 2022
  
  Published by Microsoft
  
  Publication Project
- DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions
  
  Amit Sharma, Cheng Zhang, Vasilis Syrgkanis, Emre Kiciman
  
  MSR-TR-2021-15 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication Project
- VICAUSE: Simultaneous missing value imputation and causal discovery
  
  Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Miltos Allamanis, Cheng Zhang
  
  MSR-TR-2021-14 | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Optimal transport for causal discovery
  
  Ruibo Tu, Kun Zhang, Hedvig Kjellstrom, Cheng Zhang
  
  | July 2021
  
  Published by ICML 2021 workshop on the Neglected Assumptions in Causal Inference
  
  Publication
- Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
  
  Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla
  
  arXiv:1906.00429 | June 2019
  
  Published by arXiv
  
  Publication Project
- Diagnostic Questions: The NeurIPS 2020 Education Challenge
  
  Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, Jose Miguel Hernandez Lobato, Richard Turner, Richard Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
  
  July 2020
  
  Publication
- Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
  
  Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellström, Cheng Zhang
  
  June 2019
  
  Publication
- A Causal View on Robustness of Neural Networks
  
  Cheng Zhang, Yingzhen Li
  
  June 2019
  
  Publication
- Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
  
  Anna-Lena Popkes, Hiske Overweg, Ari Ercole, Yingzhen Li, Jose Miguel Hern´andez-Lobato, Yordan Zaykov, Cheng Zhang
  
  May 2019
  
  Publication Github
- Advances in Variational Inference
  
  Cheng Zhang, Judith Butepage, Hedvig Kjellstrom, Stephan Mandt
  
  IEEE Transactions on Pattern Analysis and Machine Intelligence | August 2019, Vol 41(8): pp. 2008-2026
  
  Publication