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Balint Mate, University of Geneva.
Monday 02 December 2024, 14:00-14:30
Zoom link: https://zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09
Contact: No managers listed
0 upcoming talks View 57 archived talks
Lennard-Jones Centre
Thermodynamic Integration along energy-based Diffusion Models
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Fully non-linear neuromorphic computing with linear wave scattering
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A tour of the MaZe for classical modeling of supercapacitors
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Characterizing the electrical double layer at oxide-electrolyte interfaces using machine learning potential simulations
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Anisotropic machine learning representations for coarse-graining
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ML-MIX: A Package for Seamless Spatial Potential Mixing Inside LAMMPS
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Effective phonons for finite-temperature Raman spectroscopy from first principles: GaN and BaZrS3
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Decomposition of Response Tensors Using Point Group Representations
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Advanced materials modeling using extended Hubbard functionals
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High-throughput computational thermodynamics: a unique insight into the potential energy surface
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Advanced materials modeling using extended Hubbard functionals
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Phonons for high-throughput phase diagram prediction from ephemeral data-derived potentials
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Towards the Next Generation of Spintronics: Transport in Van der Waals Antiferromagnets
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Coexistence of Ion Diffusion and Superconductivity in Hydrides
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Merging Quantum Chemistry and Machine Learning for More Accurate Computational Models
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Tensor-Reduced Atomic Density Representations
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Physically constrained machine learning: from single-particle Hamiltonians to electronic excitations
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The stochastic self-consistent harmonic approximation (SSCHA): a non-perturbative method for incorporating quantum and anharmonic effects into nuclei dynamics from first principles
Lennard-Jones Centre
Electron-phonon and phonon-electron coupling
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Understanding strongly correlated quantum materials using embedded dynamical mean-field theory
Lennard-Jones Centre
Dynamical mean-field theory and its applications in correlated transition-metal oxides.
Lennard-Jones Centre
Creating chemical-reaction movies based on automated modeling
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Neural functional theory for inhomogeneous (non-)equilibrium fluids
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ML-guided Materials Discovery
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Exploring the Intersection Seam: Insights into Photochemical Properties
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Microscopic Mechanism of Thermally Induced Ordered-Disordered Phase transitions in Zeolitic Imidazolate Frameworks Revealed via Molecular Dynamics and Machine Learning Techniques
Lennard-Jones Centre
Embedding with auxiliary particles for strongly correlated materials
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Quantum Simulations and Topology in out-of-equilibrium Floquet Systems
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Adding functionality to machine-learning potentials: going beyond accuracy and speed
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Bilayer nickelate La3Ni2O7: interlayer electronic correlations and high-Tc superconductivity
Lennard-Jones Centre
Ion migration in halide perovskites
Lennard-Jones Centre
A different perspective on charge disproportionation/order probed by resonant X-ray scattering experiments: Insights from dynamical mean field theory
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Machine learning for molecular design of plasmonic nanosystems
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Modelling Solution Chemistry
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Advances in realistic materials modeling with the DFT+DMFT approach
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Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics
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Different charge density waves in emergent kagome materials
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New 'low-cost' electronic structure methods for large systems
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Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules
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Excited states properties of materials from many-body perturbation theory
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Real-time Subspace Methods for Hamiltonian Eigenvalue Estimation on Quantum Hardware
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Solvated electron from first principles and machine learning
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A quantum computing algorithm to speed up Metropolis sampling
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Machine learning aided fast and accurate quantum chemistry for solvated molecules
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Structures and Quantum Effects of Short Hydrogen Bonds in Proteins
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Thermal properties of MOF5: a comparison of molecular dynamics and Wigner transport approaches
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Probing Realistic Water-2D Material Interfaces via Combined Quantum and Classical Simulations
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Machine learning for nanoporous materials design
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Machine learning methods for heterogeneous catalysis
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Moving beyond screening via generative machine learning models
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Fully Quantum (Bio)Molecular Simulations: Dream or Reality?
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High-performance predictions of electron and phonon transport from first-principles
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Ab initio charge transport of ionic fluids: invariance principles and topological invariants
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Simulating the binding of the pioneer transcription factor Oct4 to the nucleosome
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A weak convergence viewpoint on invertible coarse-graining
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Exploring chemical reactions through automation and machine learning
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Clustering and learning reaction coordinates directly using atomic positions
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