Josef Teichmann
Full Professor
Researches stochastic finance and machine learning theory, including deep hedging, reservoir computing and implicit regularization of neural networks.
Josef Teichmann's lab at ETH Zurich works on learning theory & optimization. 7 papers since 2023, 2 at top venues, mostly TMLR. 7 PhD students. 15 alumni.
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 29%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 15
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 0
- 3 papers2024 · T1 1
- 3 papers2023 · T1 1
T1 venuesOtherVenues: TMLR
Research focuspaper titles that use each topic's words
- Learning theory & optimization1 paper
- implicit0 papers
- finance0 papers
- stochastic0 papers
- mathematics0 papers
Paper list
From the lab homepage.
20251 paper
- Quantitative FinanceRandomized Signature Methods in Optimal Portfolio Selection
20243 papers
- TMLR (T1)Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework
- Frontiers of Mathematical Finance (FMF), 3/1, 31-77Optimal Stopping via Randomized Neural Networks
- International Journal of Theoretical and Applied FinanceThe Jarrow and Turnbull setting revisited
20233 papers
- Frontiers in Artificial IntelligenceA case study for unlocking the potential of deep learning in assetliability- management
- TMLR (T1)Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices.
- Potential Analysis, 59 (3), 1399-1424Optimal Extension of Sobolev rough paths
Where alumni went15 listed
Apply to ETH ZurichRolling
Not announced yet
Computer Science Doctorate (D-INFK)
- Round
- Rolling (no deadline)
- Opens
- —
- GRE
- See program page
- English
- Proficiency in written and spoken English
- Fee
- See program page
Confirmed on the program page.
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Data
Checked against the lab homepage.
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- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.