Talks

Seminars and workshop talks

• September 2026: Optimal algorithmic complexity of inference in quantum kernel methods, Workshop on quantum algorithms at QuSoft.

• July 2026: Optimal algorithmic complexity of inference in quantum kernel methods, MRM Quantum seminar series at HSBC.

• June 2026: Optimal algorithmic complexity of inference in quantum kernel methods, QSL Seminar at University of Edinburgh.

• June 2026: Approximate sampling from decoded quantum interferometry via Markov chain Monte Carlo methods, QCC seminar at EPFL.

• June 2026: Tutorial on Decoded Quantum Interferometry, QIC seminar at EPFL.

• April 2026: The quest for good QML models, QCOW2 workshop at Univerisity of Warwick.

• April 2026: Potential for quantum advantage in supervised learning with quantum learning models, Qunipa Seminar at University of Palermo.

• February 2026: Tutorial on Decoded Quantum Interferometry, tutorial Seminar at AG Eisert, FU Berlin. [video]

• January 2026: Potential for quantum advantage in supervised learning with quantum learning models, IBM Q US seminar.

• July 2025: On the relation between trainability and dequantization of variational quantum learning models, Condensed Matter Seminar at ICTP Trieste.

• May 2025: Kernel-based dequantization of variational QML without Random Fourier Features, Juan Carrasquilla's group meeting at ETH Zürich.

• March 2025: Tutorial on The quantum kernel saga, Tutorial Seminar at AG Eisert, FU Berlin. [video]

• February 2025: On the relation between trainability and dequantization of variational quantum learning models, Quantum Pod seminar at UC Berkeley.

• February 2025: On the relation between trainability and dequantization of variational quantum learning models, IQIM seminar at Caltech.

• October 2024: Machine Learning on Quantum Computers: how it started vs. how it’s going, BMW QC Community.

• October 2024: On the relation between trainability and dequantization of variational quantum learning models, QMAI team seminar at TU Delft.

• October 2024: On the expressivity of embedding quantum kernels, Défi Eqip workshop at Université Paris-Saclay.

• July 2024: On the relation between trainability and dequantization of variational quantum learning models, Kappen group seminar.

• July 2024: On the relation between trainability and dequantization of variational quantum learning models, QTI Journal Club at CERN.

• April 2024: On the expressivity of embedding quantum kernels, GIQ Seminar at UAB.

• February 2024: On the expressivity of embedding quantum kernels, IBM Q UK seminar.

• January 2024: On the expressivity of embedding quantum kernels, QAISG QML seminar. [video]

• December 2023: On the expressivity of embedding quantum kernels, aQa seminar at Leiden University.

• November 2023.XI: On the expressivity of embedding quantum kernels, QIC seminar at EPFL.

• October 2023: Understanding quantum machine learning also requires rethinking generalization, Google Quantum AI QML meeting.

• October 2023: Understanding quantum machine learning also requires rethinking generalization, QAISG QML seminar. [video]

• September 2023: Understanding quantum machine learning also requires rethinking generalization, QUANTIC group seminar.

• April 2023: Exploiting symmetry in variational quantum machine learning, Machine Learning and (Quantum) Physics workshop.

• January 2023: Exploiting symmetry in variational quantum machine learning, QUANTIC group seminar.

• November 2021: Encoding-dependent generalization bounds for parametrized quantum circuits, Tomamichel Group Seminar.