Anji Liu
NUS Presidential Young Professor
Develops tractable probabilistic models and deep generative models, with work on tractable inference and controllable generation under constraints.
Anji Liu's lab at NUS works on probabilistic & causal inference, generative & foundation models and efficient training & inference. 6 papers since 2023, 4 at top venues, mostly ICML and ICLR. Applications close .
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 67%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 1 · collecting
- 1 papers2025 · T1 1
- 2 papers2024 · T1 2
- 1 papers2023 · T1 0
T1 venuesOtherVenues: ICML, ICLR, NeurIPS
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference4 papers
- tractable2 papers
- Generative & foundation models1 paper
- Efficient training & inference1 paper
- constraints0 papers
Paper list
From the lab homepage.
20262 papers
- ICML (T1)Breaking the Factorization Barrier in Diffusion Language Models (opens in a new tab)
- The Twenty-Ninth Annual Conference on Artificial Intelligence and Statistics (AISTATS)Oral presentationRethinking Probabilistic Circuit Parameter Learning (opens in a new tab)
20251 paper
20242 papers
20231 paper
- The Eleventh International Conference on Learning Representations (ICLR)Oral presentationScaling Up Probabilistic Circuits by Latent Variable Distillation (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NUSFall 2027
School of Computing PhD in Computer Science
- Round
- Main
- Opens
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- GRE
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- English
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- Fee
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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.
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- The lab homepage
- Members
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- Alumni
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Tiers are venue classifications, not lab rankings.
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