Nicolas Flammarion
Associate Professor
Leads the Theory of Machine Learning Laboratory, studying optimization and the training dynamics of neural networks.
Nicolas Flammarion's lab at EPFL works on learning theory & optimization and signal processing & information theory. 5 papers since 2023, 2 at top venues, mostly NeurIPS. 8 PhD students and 1 master's student. 16 alumni. Applications close .
At a glance
- papers, 2023–2026
- 1/ year
- at T1 venues
- 40%
- PhD students
- 8
- MS students
- 1
- alumni listed
- 16
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 1 papers2024 · T1 0
- 4 papers2023 · T1 2
T1 venuesOtherVenues: NeurIPS
Research focuspaper titles that use each topic's words
- dynamics1 paper
- Learning theory & optimization0 papers
- Signal processing & information theory0 papers
- studying0 papers
- communication sciences0 papers
Paper list
From the lab homepage.
20241 paper
- Proceedings of the International Conference on Artificial Intelligence and Statistics (AIS- TATS)Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks
20234 papers
- NeurIPS (T1)(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability
- —Model agnostic methods meta-learn despite misspecifications
- —Penalising the biases in norm regularisation enforces sparsity
- NeurIPS (T1)Saddle-to-Saddle Dynamics in Diagonal Linear Networks
Where alumni went16 listed, 0% to industry
Industry 0Academia 1
Also to
- RWTH Aachen University
Apply to EPFLFall 2027
EDIC Computer and Communication Sciences PhD
- Round
- Round 1
- Opens
- —
- GRE
- optional
- English
- TOEFL 100 / IELTS 7.0
- Fee
- none
Confirmed on the program page.
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Data
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- Papers
- The lab homepage
- Members
- Lab homepage
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