1 citations · 1 across the 9 of their papers we have counts for
9 papers
On Moment-Based Recovery of Measures with Atomic and Continuous Parts
Ruben Karapetyan, Shenyuan Ma, Aleš Wodecki +1
Recovering probability measures from moments is a central theme in statistics and optimization. In particular, we focus on the recovery of measures from moments and pseudo-moments,…
Penalised and constrained geodesics in geometric control theory
Rufus Lawrence, Aleš Wodecki, Johannes Aspman +1
In many problems in optimal control, one seeks to minimise an objective function subject to constraints on the velocity of the system. Imposing these constraints directly -- the ``…
Time evolution of controlled many-body quantum systems with matrix product operators
Llorenç Balada Gaggioli, Jakub Mareček
We present a method for describing the time evolution of many-body controlled quantum systems using matrix product operators (MPOs). Existing techniques for solving the time-depend…
Deep Learning as the Disciplined Construction of Tame Objects
Gilles Bareilles, Allen Gehret, Johannes Aspman +2
One can see deep-learning models as compositions of functions within the so-called tame geometry. In this expository note, we give an overview of some topics at the interface of ta…
Unitary Gate Synthesis via Polynomial Optimization
Llorenç Balada Gaggioli, Denys I. Bondar, Jiri Vala +2
Quantum optimal control plays a crucial role in the development of quantum technologies, particularly in the design and implementation of fast and accurate gates for quantum comput…
Undecidable problems associated with variational quantum algorithms
Georgios Korpas, Vyacheslav Kungurtsev, Jakub Mareček
Variational Quantum Algorithms (VQAs), such as the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA), are widely studied as candidates…
Geometric quantum control and the random Schrödinger equation
Rufus Lawrence, Aleš Wodecki, Johannes Aspman +2
Understanding and mitigating noise in quantum systems is a fundamental challenge in achieving scalable and fault-tolerant quantum computation. Error modeling for quantum systems ca…
Bias Detection via Maximum Subgroup Discrepancy
Jiří Němeček, Mark Kozdoba, Illia Kryvoviaz +2
Bias evaluation is fundamental to trustworthy AI, both in terms of checking data quality and in terms of checking the outputs of AI systems. In testing data quality, for example, o…
Causal Learning in Biomedical Applications: Krebs Cycle as a Benchmark
Xiaoyu He, Petr Ryšavý, Jakub Mareček
Learning causal relationships from time series data is an important but challenging problem. Existing synthetic datasets often contain hidden artifacts that can be exploited by cau…