Cheng Zhang

发表

Educational Question Mining At Scale: Prediction, Analysis and Personalization

Sebastian Tschiatschek, Zichao Wang, Richard G. Baraniuk, 2021, AAAI.

Deep End-to-end Causal Inference

Emre Kıcıman, Adam Foster, Wenbo Gong, 2022, ArXiv.

A Causal View on Robustness of Neural Networks pdf

Kun Zhang, Yingzhen Li, Cheng Zhang, 2020, NeurIPS.

CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

Desi R. Ivanova, Tom Rainforth, Adam Foster, 2023, ArXiv.

HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals

Sebastian Tschiatschek, Cheng Zhang, Richard E. Turner, 2019, AABI.

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

Sam Devlin, Sebastian Tschiatschek, Katja Hofmann, 2019, NeurIPS.

AMRL: Aggregated Memory For Reinforcement Learning

Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, 2020, ICLR.

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions pdf

Vasilis Syrgkanis, Cheng Zhang, Emre Kiciman, 2021, ArXiv.

VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data pdf

Sebastian Tschiatschek, Cheng Zhang, Richard E. Turner, 2020, NeurIPS.

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2018, ICML.

Local Constraint-Based Causal Discovery under Selection Bias

J. Mooij, Philip Versteeg, Cheng Zhang, 2022, CLeaR.

Partial VAE for Hybrid Recommender System

José Miguel Hernández-Lobato, S. Nowozin, Noam Koenigstein, 2018 .

Contextual HyperNetworks for Novel Feature Adaptation pdf

Sebastian Tschiatschek, Richard E. Turner, Angus Lamb, 2021, ArXiv.

Meta-Learning Divergences of Variational Inference

Christopher De Sa, Yingzhen Li, Sam Devlin, 2020, 2007.02912.

Large-Scale Educational Question Analysis with Partial Variational Auto-encoders pdf

Sebastian Tschiatschek, Zichao Wang, Simon Woodhead, 2020, ArXiv.

Meta-Learning for Variational Inference pdf

Sam Devlin, Cheng Zhang, Ruqi Zhang, 2019, ArXiv.

Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2019, NeurIPS.

Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model pdf

Sebastian Nowozin, Sebastian Tschiatschek, Cheng Zhang, 2019, ArXiv.

A Study on Efficiency in Continual Learning Inspired by Human Learning pdf

Cheng Zhang, Angus Lamb, Yingzhen Li, 2020, ArXiv.

Diagnostic Questions: The NeurIPS 2020 Education Challenge pdf

Zichao Wang, Simon Woodhead, Simon Peyton Jones, 2020, ArXiv.

Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge

Richard E. Turner, José Miguel Hernández-Lobato, Simon L. Peyton Jones, 2021, NeurIPS.

Causally Constrained Data Synthesis for Private Data Release pdf

Somesh Jha, Shruti Tople, Varun Chandrasekaran, 2021, ArXiv.

Simultaneous Missing Value Imputation and Structure Learning with Groups

Simon L. Peyton Jones, Wenbo Gong, Nick Pawlowski, 2021, NeurIPS.

VICause: Simultaneous Missing Value Imputation and Causal Discovery with Groups pdf

Pablo Morales-Alvarez, Angus Lamb, Cheng Zhang, 2021, ArXiv.

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

José Miguel Hernández-Lobato, S. Nowozin, Konstantina Palla, 2018, ICML.

Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care pdf

Yordan Zaykov, José Miguel Hernández-Lobato, Cheng Zhang, 2019, ArXiv.

CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

Desi R. Ivanova, Tom Rainforth, Adam Foster, 2023, ICML.

DRIFT: Deep Reinforcement Learning for Functional Software Testing pdf

José Miguel Hernández-Lobato, Levent Özgür, Cheng Zhang, 2020, ArXiv.

ODIN: Optimal Discovery of High-value INformation Using Model-based Deep Reinforcement Learning

Cheng Zhang, Sara Zannone, José Miguel Hernández Lobato, 2019 .

Reinforcement Learning with Efficient Active Feature Acquisition pdf

Sebastian Tschiatschek, Cheng Zhang, Sinno Jialin Pan, 2020, ArXiv.

NeurIPS Competition Instructions and Guide: Causal Insights for Learning Paths in Education

Wenbo Gong, Nick Pawlowski, Zichao Wang, 2022, 2208.12610.

Meta-Learning for Variational Inference

Chris De Sa, Yingzhen Li, Sam Devlin, 2019, ArXiv.