Journal Club for Quantum Physics and Machine Learning
Schedule
Next Journal Club Meeting: TBA
Speaker: TBA
Affiliation: TBA
Title: TBA
Reference: TBA
URL: TBA
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Upcoming Journal Club meetings:
| Date | Time | Speaker | Affiliation | Reference |
| TBA | TBA | TBA | TBA | TBA |
Past Journal Club Meetings:
| Date | Time | Speaker | Affiliation | Reference |
| 27th June 2023 | 5:30pm CET | João Augusto Sobral | University of Innsbruck |
Machine learning microscopic form of nematic order in twisted double-bilayer graphene |
| 30th May 2023 | 5:30pm CET | Valeria Cimini | Sapienza Università di Roma | Deep reinforcement learning for quantum multiparameter estimation |
| 9th May 2023 | 5:30pm CET | Marcel Rodekamp | Forschungszentrum Jülich | Mitigating the Hubbard Sign Problem. A Novel Application of Machine Learning |
| 2nd May 2023 | 5:30pm CET | Laura Lewis | California Institute of Technology | Improved machine learning algorithm for predicting ground state properties |
| 18th April 2023 | 5:30pm CET | Santiago Acevedo | Institute of Physics of La Plata / SISSA | Autoregressive networks as a variational Ansatz |
| 4th April 2023 | 5:30pm CET | Pietro Novelli | Istituto Italiano di Tecnologia | Learning dynamics systems: an example from open quantum system dynamics |
| 21st March 2023 | 5:30pm CET | Frederik Wilde | Freie Universität Berlin | Scalably learning quantum many-body Hamiltonians from dynamical data |
| 13th December 2022 | 6:00pm CET | Michael Goerz | Stanford University | Quantum Optimal Control via Semi-Automatic Differentiation |
| 29th November 2022 | 5:30pm CET | Abigail McClain Gomez | Harvard University | Reconstructing quantum states using basis-enhanced Born machines |
| 15th November 2022 | 5:30pm CET | Nicolas Sadoune | University of Munich / MCQST | Unsupervised Interpretable Learning of Phases From Many-Qubit Systems |
| 1st November 2022 | 5:30pm CET | Flavia Alejandra Gómez Albarracín | University of La Plata | Machine learning techniques to construct detailed phase diagrams for skyrmion system |
| 18th October 2022 | 5:30pm CET | Riccardo Fabbricatore | Skolkovo Institute of Science and Technology | Gradient dynamics in reinforcement learning |
| 4th October 2022 | 5:30pm CET | Bogdan Zviazhynski | University of Cambridge | Unveil the unseen: Exploit information hidden in noise |
| 21st June 2022 | 5:30pm CET | Javier Robledo Moreno | Flatiron Institute / NYU |
Fermionic wave functions from neural-network constrained hidden states |
| 7th June 2022 | 5:30pm CET | Francesco Carnazza | Universität Tübingen | |
| 24th May 2022 | 5:30pm CET | Niklas Käming | Universität Hamburg |
Unsupervised machine learning of topological phase transitions from experimental data |
| 10th May 2022 | 5:30pm CET | Julian Arnold | University of Basel |
Replacing neural networks by optimal analytical predictors for the detection of phase transitions |
| 26th April 2022 | 5:30pm CET | Katerina Gratsea | ICFO | |
| 12th April 2022 | 5:30pm CET | Anna Dawid | University of Warsaw / ICFO |
Hessian-based toolbox for reliable and interpretable machine learning in physics |
| 12th December 2021 | 5:30pm CET | Jonathon Brown | Queen's University Belfast | Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems |
| 7th December 2021 | 5:30pm CET | M. Michael Denner | University of Zürich | Efficient learning of a one-dimensional density functional theory |
| 23rd November 2021 | 5:30pm CET | Robert Huang | California Institute of Technology | Provably efficient machine learning for quantum many-body problems |
| 9th November 2021 | 5:30pm CET | Paolo Andrea Erdman | Freie Universität Berlin | Identifying optimal cycles in quantum thermal machines with reinforcement-learning |
| 26th October 2021 | 5:30pm CET | Maciej Koch-Janusz | University of Zurich / University of Chicago | Relevant operators and symmetries through the lens of real-space mutual information |
| 12th October 2021 | 5:30pm CET | Moritz Reh | Heidelberg University | Time-dependent variational principle for open quantum systems with artificial neural networks |
| 15th June 2021 | 4:30pm CET | Nishad Maskara | Harvard University | A learning algorithm with emergent scaling behavior for classifying phase transitions |
| 1st June 2021 | 4:30pm CET | Rouven Koch | Aalto University | Neural network enhanced hybrid quantum many-body dynamical distributions |
| 18th May 2021 | 4:30pm CET | Wei Chen | PUC Rio de Janeiro | A supervised learning algorithm for interacting topological insulators based on local curvature |
| 4th May 2021 | 4:30pm CET | Agnes Valenti | ETH Zürich | Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics |
| 20th April 2021 | 4:30pm CET | Rui Lin | ETH Zürich |
Minimal model of permutation symmetry in unsupervised learning |
| 6th April 2021 | 4:30pm CET | Miriam Büttner | University of Freiburg |
Learning Potentials of Quantum Systems using Deep Neural Networks |
| 23rd March 2021 | 4:30pm CET | Luuk Coopmans | Trinity College Dublin/Dublin Institute for Advanced Studies | Protocol Discovery for the Quantum Control of Majoranas by Differential Programming and Natural Evolution Strategies |
| 9th March 2021 | 4:30pm CET | Axel Lode | University of Freiburg |
Interpretable Phase Detection and Classification with Persistent Homology |
| 23rd February 2021 | 4:30pm CET | Evert van Nieuwenburg | University of Copenhagen | A NEAT Quantum Error Decoder |
| 9th February 2021 | 3pm CET | Shahnawaz Ahmed | Chalmers University of Technology | Classification and reconstruction of optical quantum states with deep neural networks |
| 26th January 2021 | 3pm CET | Julian Arnold | University of Basel | Interpretable and unsupervised phase classification |
| 12th January 2021 | 3pm CET | Paolo Molignini | University of Cambridge |
Scientific intuition inspired by machine learning generated hypotheses |


