Cheng Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 42

Top Venues

Royal Institute of Technology, Stockholm, Sweden (PHD)

Education History

Royal Institute of Technology, Stockholm, Sweden

PHD

Publications

Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR (2024)
Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery. NeurIPS (2023)
Marcus Klasson, Hedvig Kjellström, Cheng Zhang
Learn the Time to Learn: Replay Scheduling in Continual Learning. Trans. Mach. Learn. Res. 2023 (2023)
Wenbo Gong, Joel Jennings, Cheng Zhang, Nick Pawlowski
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise. ICLR (2023)
Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang
Simultaneous Missing Value Imputation and Structure Learning with Groups. NeurIPS (2022)
Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang
Optimal transport for causal discovery. CoRR (2022)
Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang
Optimal Transport for Causal Discovery. ICLR (2022)
Chao Ma, Cheng Zhang
Identifiable Generative models for Missing Not at Random Data Imputation. NeurIPS (2021)
Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li
Sparse Uncertainty Representation in Deep Learning with Inducing Weights. NeurIPS (2021)
Cheng Zhang, Kun Zhang, Yingzhen Li
A Causal View on Robustness of Neural Networks. NeurIPS (2020)
Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang
How do fair decisions fare in long-term qualification? NeurIPS (2020)
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
Using Variational Multi-view Learning for Classification of Grocery Items. Patterns 1 (8) (2020)
Cheng Zhang, Kun Zhang, Yingzhen Li
A Causal View on Robustness of Neural Networks. CoRR (2020)
Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang
How Do Fair Decisions Fare in Long-term Qualification? CoRR (2020)
Charles Hamesse, Ruibo Tu, Paul Ackermann, Hedvig Kjellström, Cheng Zhang
Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation. MLHC (2019)
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
A Hierarchical Grocery Store Image Dataset With Visual and Semantic Labels. WACV (2019)
Cheng Zhang, Judith Bütepage, Hedvig Kjellström, Stephan Mandt
Advances in Variational Inference. IEEE Trans. Pattern Anal. Mach. Intell. 41 (8) (2019)
Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellström, Cheng Zhang
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation. CoRR (2019)
Marcus Klasson, Cheng Zhang, Hedvig Kjellström
A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels. CoRR (2019)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory. CoRR (2019)
Cheng Zhang, Cengiz Öztireli, Stephan Mandt, Giampiero Salvi
Active Mini-Batch Sampling Using Repulsive Point Processes. AAAI (2019)
Ruibo Tu, Cheng Zhang, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang
Causal Discovery in the Presence of Missing Data. AISTATS (2019)
Ruibo Tu, Kun Zhang, Bo C. Bertilson, Hedvig Kjellström, Cheng Zhang
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation. NeurIPS (2019)
Cheng Zhang, Cengiz Öztireli, Stephan Mandt, Giampiero Salvi
Active Mini-Batch Sampling using Repulsive Point Processes. CoRR (2018)
Tianfan Fu, Cheng Zhang, Stephan Mandt
Continuous Word Embedding Fusion via Spectral Decomposition. CoNLL (2018)
Ruibo Tu, Cheng Zhang, Paul Ackermann, Hedvig Kjellström, Kun Zhang
Causal discovery in the presence of missing data. CoRR (2018)
Charles Hamesse, Hedvig Kjellström, Paul Ackermann, Cheng Zhang
Simultaneous measurement imputation and outcome prediction for Achilles tendon rupture rehabilitation. AIH@IJCAI (2018)
Charles Hamesse, Ruibo Tu, Paul Ackermann, Hedvig Kjellström, Cheng Zhang
Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation. CoRR (2018)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Perturbative Black Box Variational Inference. CoRR (2017)
Cheng Zhang, Hedvig Kjellström, Stephan Mandt
Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes. UAI (2017)
Cheng Zhang, Hedvig Kjellström, Stephan Mandt
Stochastic Learning on Imbalanced Data: Determinantal Point Processes for Mini-batch Diversification. CoRR (2017)
Cheng Zhang, Judith Bütepage, Hedvig Kjellström, Stephan Mandt
Advances in Variational Inference. CoRR (2017)
Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
Perturbative Black Box Variational Inference. NIPS (2017)
Marcus Klasson, Kun Zhang, Bo C. Bertilson, Cheng Zhang, Hedvig Kjellström
Causality Refined Diagnostic Prediction. CoRR (2017)
Cheng Zhang, Hedvig Kjellström, Bo C. Bertilson
Diagnostic Prediction Using Discomfort Drawings. CoRR (2016)
An Qu, Cheng Zhang, Paul Ackermann, Hedvig Kjellström
Bridging Medical Data Inference to Achilles Tendon Rupture Rehabilitation. CoRR (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo C. Bertilson
Diagnostic Prediction Using Discomfort Drawings with IBTM. MLHC (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek
Inter-battery Topic Representation Learning. ECCV (8) (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo C. Bertilson
Diagnostic Prediction Using Discomfort Drawings with IBTM. CoRR (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek
Inter-Battery Topic Representation Learning. CoRR (2016)
Cheng Zhang, Hedvig Kjellström
How to Supervise Topic Models. ECCV Workshops (2) (2014)
Cheng Zhang, Dan Song, Hedvig Kjellström
Contextual modeling with labeled multi-LDA. IROS (2013)
Cheng Zhang, Carl Henrik Ek, Xavi Gratal, Florian T. Pokorny, Hedvig Kjellström
Supervised Hierarchical Dirichlet Processes with Variational Inference. ICCV Workshops (2013)
Cheng Zhang, Hedvig Kjellström
Multi-Class Detection and Segmentation of Objects in Depth CoRR (2013)
Cheng Zhang, Carl Henrik Ek, Hedvig Kjellström
Factorized Topic Models ICLR (Workshop Poster) (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Cheng Zhang