Publications and Preprints

Doctoral Thesis - Machine Learning in Finance: Applications of Continuous Depth and Randomized Neural Networks
Examiner: Prof. Dr. Josef Teichmann and Co-Examiner: Prof. Dr. Antoine Jacquier
Defended on September 15th, 2021

Optimal Stopping via Randomized Neural Networks
Calypso Herrera, Florian Krach, Pierre Ruyssen, Josef Teichmann
Preprint (submitted), 2021 [paper, code, slides]

Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
International Conference on Learning Representations (ICLR), 2021 [paper, code]

Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices
Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann
Preprint (submitted), 2020 [paper, code]

Estimating Full Lipschitz Constants of Deep Neural Networks
Calypso Herrera, Florian Krach, Josef Teichmann
Preprint, 2020 [paper]

Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization
Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen
Transaction on Neural Networks and Learning systems (accepeted for publication), 2021 [paper, code]

Parallel American Monte Carlo
Calypso Herrera, Louis Paulot
Preprint, 2016 [paper]
Google Scholar and GitHub

Past Talks

  • Oxford ETH Workshop, 2022, Zurich (Switzerland), 20-21.06.2022. Optimal Stopping via Randomized Neural Networks.
  • SIAM Annual Meeting, 2021, Virtual, 19-23.07.2021. Optimal Stopping via Randomized Neural Networks.
  • 10th General AMaMeF Conference, 2021, Virtual Padova (Italy), 22-25.06.2021. Optimal Stopping via Randomized Neural Networks.
  • Oberwolfach Workshop 2020, Virtual Oberwolfach (Germany), 25-21.10.2020. Optimal Stopping via Randomized Neural Networks.
  • Josef's Friday Seminar, Virtual Zurich (Switzerland), 01.05.2020. Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering.
  • FPWZ Seminar, Zurich (Switzerland), 10-11.10.2019. Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices.
  • FWZ Seminar, Padova (Italy), 16-17.05.2019. Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization.
  • FWZ Seminar, Vienna (Austria), 15-16.01.2018. Parallel American Monte Carlo.
  • Bachelier Colloquium 2017, Métabief (France), 16-21.1.2017. Parallel American Monte Carlo.
  • FWZ Seminar, Freiburg (Germany), 30.11-2.12.2016. Parallel American Monte Carlo.
  • Post/Doctoral Seminar in Mathematical Finance, Zurich (Switzerland), 25.10.2016. Convexity adjustment on terminal rate models.
  • Imperial ETH Workshop on Mathemetical Finance 2016, Zurich (Switzerland), 26-28.10.2016. Parallel American Monte Carlo.