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26 MIN-Fakultät Machine Learning in Natural Sciences: From Quantum Physics to Nanoscience and Structural Biology 2022 Michel Frising, Claudia Draxl, Seastian Wetzel et al. 22.09.2022 Tackling Multimodal Device Distributions in Inverse Photonic Design: Lessons learned from Invertible Neural Networks Michel Frising 22.09.2022 Machine-learning from heterogenous data: dream or reality? Claudia Draxl 22.09.2022 Revealing physical concepts learned by artificial neural networks Seastian Wetzel 22.09.2022 Towards an Artificial Muse for new Ideas and Understanding in the natural Sciences Mario Krenn 21.09.2022 Deep Learning for Topological Materials Marcin Płodzień 21.09.2022 Autonomous Materials Research and Discovery at NIST Aaron Gilad Kusne 21.09.2022 Tensor networks and efficient descriptions of classical data Ivan Kukuljan 21.09.2022 What do neural networks learn? On the interplay between data structure and representation learning Sebastian Goldt 21.09.2022 Quantum flows neural network for variational solutions of the Schrödinger equation Andrey Yachmenev 21.09.2022 OpenFold: Democratizing access to modeling biomolecules and their interactions Mohammed Alquraishi 21.09.2022 Learning Conductance: Gaussian Process Regression for Molecular Electronics Michael Deffner 21.09.2022 Chiral Structure Classification by a Convolutional Neural Network Peer Kasten 21.09.2022 AI usage in Structural Biology Dr. Andrea Thorn 20.09.2022 Data-Enhanced Variational Monte Carlo with Neural Network Quantum States Stefanie Czischek 20.09.2022 Unraveling Quantum Scrambling with Neural Networks Jan Olle 20.09.2022 Machine learning of thermodynamic observables in lattice quantum field theory Kim Nicoli 20.09.2022 Physical Parametrisations of Mixed Quantum States with Deep Neural Networks Filippo Vicentini 20.09.2022 Circuit complexity through phase transitions and its consequences in quantum state preparation David Zueco 20.09.2022 Quantum physics data as a playground for machine learning Evert van Nieuwenburg 20.09.2022 Solving quantum and classical dissipative dynamics with artificial neural networks Martin Gärtner 20.09.2022 Insights into quantum many-body systems through Hamiltonian reconstruction Annabelle Bohrdt 19.09.2022 PeakNet: Peak Finding for Serial Crystallography Shah Nawaz 19.09.2022 Robust Image Descriptor for Machine Learning based Data Reduction in Crystallography Vahid Rahmani 19.09.2022 Machine Learning for Accelerated Molecular Discovery Pascal Friedrich 19.09.2022 Unraveling heterogeneous diffusion in single particle trajectories Borja Requena 19.09.2022 Creating community driven challenges to advance Science Gorka Mun˜oz-Gil 19.09.2022 Robust quantum dot charge autotuning with Bayesian Neural Networks Victor Yon 19.09.2022 Online adaptive estimation of decoherence timescales for a single qubit Muhammad Junaid Arshad 19.09.2022 Disentangling Multi-Qubit States using Reinforcement Learning Marin Bukov 19.09.2022 Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks Friederike Metz Alle Videos...