Ricardo Silva
Professor of Statistical Machine Learning and Data Science
Researches causal inference and graphical models in statistical machine learning.
Ricardo Silva's lab at UCL works on learning theory & optimization, probabilistic & causal inference and efficient training & inference. 9 papers since 2023, 5 at top venues, mostly NeurIPS and AISTATS.
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 56%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 3 papers2025 · T1 1
- 4 papers2024 · T1 3
- 2 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, AISTATS, IJCNN, UAI
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference5 papers
- Learning theory & optimization2 papers
- Efficient training & inference0 papers
- graphical models0 papers
- statistical0 papers
Paper list
From DBLP.
20253 papers
- AISTATS (T1)BudgetIV: Optimal Partial Identification of Causal Effects with Mostly Invalid Instruments (opens in a new tab)
- IJCNNCausal Analysis of Intellectual Complexity in Software Engineering (opens in a new tab)
- Found. Trends Optim.Causal Machine Learning: A Survey and Open Problems (opens in a new tab)
20244 papers
- UAI (T1)Bounding causal effects with leaky instruments (opens in a new tab)
- NeurIPS (T1)Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models (opens in a new tab)
- CLeaRPragmatic Fairness: Developing Policies with Outcome Disparity Control (opens in a new tab)
- NeurIPS (T1)Structured Learning of Compositional Sequential Interventions (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UCLFall 2027
Not announced yet
Computer Science MPhil/PhD
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- USMichigan
Lei Ying
- Reinforcement learning
- USCMU
Eric Xing
- Generative & foundation models
- SGNTU
Siu Lun Chau
- Learning theory & optimization
- USNYU
Todd Gureckis
- Data management & big data
- SGNUS
Roger Zimmermann
- Time series, anomaly & spatio-temporal data
- GBUCL
Siddharth Swaroop
- Probabilistic & causal inference
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- 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
- DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.