Stephen Roberts
Professor of Machine Learning
Leads the Machine Learning Research Group on Bayesian machine learning and its applications in science and finance.
Stephen Roberts's lab at Oxford works on probabilistic & causal inference. 11 papers since 2023, 2 at top venues, mostly JMLR and Neural Networks. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 18%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 0
- 3 papers2024 · T1 1
- 5 papers2023 · T1 1
T1 venuesOtherVenues: JMLR, Neural Networks, NeurIPS
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference1 paper
- bayesian1 paper
- finance0 papers
- engineering science0 papers
- applications0 papers
Paper list
From DBLP.
20262 papers
20251 paper
20243 papers
- Nat. Mac. Intell.Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers (opens in a new tab)
- ICAIFDeep Learning for Options Trading: An End-To-End Approach (opens in a new tab)
- JMLR (T1)Iterate Averaging in the Quest for Best Test Error (opens in a new tab)
20235 papers
- Algorithmic FinanceGuidelines for building a realistic algorithmic trading market simulator for backtesting while incorporating market impact: Agent-Based Strategies in Neural Network Format, Ecosystem Dynamics & Detection (opens in a new tab)
- NeurIPS (T1)Nonparametric Boundary Geometry in Physics Informed Deep Learning (opens in a new tab)
- EntropyOn Sequential Bayesian Inference for Continual Learning (opens in a new tab)
- Trans. Mach. Learn. Res.On the Sample Complexity of Lipschitz Constant Estimation (opens in a new tab)
- CoLLAsThe Effectiveness of World Models for Continual Reinforcement Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- CNZhejiang
Zhengxing Huang
- Reinforcement learning
- USUCLA
Aditya Grover
- Reinforcement learning
- GBCambridge
Damon Wischik
- Probabilistic & causal inference
- GBOxford
Mark van der Wilk
- Probabilistic & causal inference
- SGNTU
Yew-Soon Ong
- Learning theory & optimization
- GBEdinburgh
Amos Storkey
- Reinforcement learning
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.
- The lab site and the paper record do not agree.
- Collected
- Verified
- Papers
- DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
Oxfordcloses