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H. Pham

28 papers hereh-index 508.3k citations165 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author2
  • middle author8
  • last author15

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • math.PR14
  • math.OC7
  • q-fin.CP3
  • q-fin.PM3
  • stat.ML1
same name
  • H. Pham — 88 papers
  • H. Pham — 20 papers, h 19
  • H. Pham — 11 papers, h 12
  • H. Pham — 11 papers, h 4
  • H. Pham — 10 papers, h 9
  • H. Pham — 8 papers, h 14

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20042023
most citedOn some recent aspects of stochastic control and their applications

90 citations · 165 across the 16 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

math.OC2019

Integral operator Riccati equations arising in stochastic Volterra control problems

Eduardo Abi Jaber, Enzo Miller, Huyen Pham

We establish existence and uniqueness for infinite dimensional Riccati equations taking values in the Banach space L 1 (μ ⊗ μ) for certain signed matrix measures μ wh…

math.OC2019

Linear--Quadratic control for a class of stochastic Volterra equations: solvability and approximation

Eduardo Abi Jaber, Enzo Miller, Huyên Pham

We provide an exhaustive treatment of Linear-Quadratic control problems for a class of stochastic Volterra equations of convolution type, whose kernels are Laplace transforms of ce…

math.OC2019

Neural networks-based backward scheme for fully nonlinear PDEs

Huyen Pham, Xavier Warin, Maximilien Germain

We propose a numerical method for solving high dimensional fully nonlinear partial differential equations (PDEs). Our algorithm estimates simultaneously by backward time induction…

math.PR2019

Deep backward schemes for high-dimensional nonlinear PDEs

Côme Huré, Huyên Pham, Xavier Warin

We propose new machine learning schemes for solving high dimensional nonlinear partial differential equations (PDEs). Relying on the classical backward stochastic differential equa…

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