Peng Cui
Associate Professor (Tenured)
Works on causally inspired stable learning, combining causal statistics with machine learning, and on big-data analysis.
Peng Cui's lab at Tsinghua works on probabilistic & causal inference, learning theory & optimization and visualization & visual analytics. 20 papers since 2023, 18 at top venues, mostly ICML and CVPR. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 90%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 6 papers2024 · T1 6
- 14 papers2023 · T1 12
T1 venuesOtherVenues: ICML, CVPR, AAAI, AISTATS, ICCV
Research focuspaper titles that use each topic's words
- Learning theory & optimization4 papers
- Probabilistic & causal inference0 papers
- Visualization & visual analytics0 papers
- inspired0 papers
- big-data analysis0 papers
Paper list
From the lab homepage.
20246 papers
- ICML (T1)Domain-wise Data Acquisition to Improve Performance under Distribution Shift
- AISTATS (T1)Enhancing Distributional Stability among Sub-populations
- ICML (T1)Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
- CVPR (T1)Rethinking the Evaluation Protocol of Domain Generalization
- ICML (T1)Stability Evaluation via Distributional Perturbation Analysis
- Nature Machine Intelligence (T1)Stable Cox Regression for Survival Analysis under Distribution Shifts
202314 papers
- ICML (T1)Competing for Shareable Arms in Multi-Player Multi-Armed Bandits
- AAAI (T1)Covariate-Shift Generalization via Random Sample Weighting
- CLeaRFactual Observation Based Heterogeneity Learning for Counterfactual Prediction
- ICCV (T1)Flatness-Aware Minimization for Domain Generalization
- TPAMI (T1)Generalizing graph neural networks on out-of-distribution graphs
- CVPR (T1)Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization
- ICLR (T1)Measure the Predictive Heterogeneity
- CVPR (T1)NICO++: Towards better bechmarks for Out-of-Distribution Generalization
- The WebConfOffline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping
- NeurIPS (T1)On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
- ICML (T1)Propensity Matters: Measuring and Enhancing Balancing for Recommendation
- ICML (T1)Provably Invariant Learning without Domain Information
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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Your notes
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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
- Not collected
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