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Robert-Jan Slager.
Monday 12 October 2020, 17:00-17:30
virtual ZOOM meeting ID: 263 591 6003, https://zoom.us/j/2635916003
Contact: No managers listed
0 upcoming talks View 23 archived talks
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Unsupervised Machine Learning and Band Topology
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Solving the electronic Schrödinger equation with deep learning
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Neural network quantum states, from lattice models to quantum chemistry and quantum computing
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Journal club: Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Unsupervised attention-guided atom-mapping
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Machine learning and the University
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Statistical learning for phase-change memory materials
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Machine learning an interatomic potential without (much) human effort
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Introduction to Gaussian processes and Modulated Bayesian Optmisation
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Applications of Machine Learning in Lattice QCD
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Combining scalar and vector learning to predict molecular dipole moments
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Tutorial: Mapping the space of materials and molecules
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Neural network potentials in theory and practice
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Exact Learning
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Representing potential energy surfaces with neural networks
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Transformer-based Chemical Reaction Prediction and Synthesis Planning
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Representing many-body wave functions using Gaussian processes
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Noisy, sparse, nonlinear: Navigating the Bermuda Triangle of physical inference with deep filtering
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Discovering new materials by detecting modules in atomic networks
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
A clustering analysis of structural heterogeneity in supercooled liquids
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Inverse Design of Simple Liquids using Machine Learning and the Ornstein-Zernike Equation
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Deciphering correlations in concentrated electrolytes using unsupervised learning
Machine learning in Physics, Chemistry and Materials discussion group (MLDG)
Deep Generative Models of Molecules in 3D Space
Please see above for contact details for this list.