Recorded Talks

Felix Faber – Representing Materials; an Overview and Covering New Ground
https://www.youtube.com/watch?v=HIdm03tFwo8&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Matthias Rupp – Introduction to Learning with Kernels
https://www.youtube.com/watch?v=vffSSlLEy2Q&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Anton Bochkarev – Structural Descriptors and Atomic Cluster Expansion Basis
https://www.youtube.com/watch?v=P5cfUl1lGp0&ab_channel=ICTPCondensedMatterandStatisticalPhysics

‪Milica Todorović‬ – Materials-structure Property Mapping with Kernel Based Methods
https://www.youtube.com/watch?v=oeY6Gez9NOQ&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Alessandro Laio – Automatic Topography of Multidimensional Probability Densities
https://www.youtube.com/watch?v=2mJu-pbRNdE&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Kristof Schütt – Neural Networks for Materials Applications
https://www.youtube.com/watch?v=HcEh3YUtCSM&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Franco Pellegrini – Training Neural Network Potentials with PANNA
https://www.youtube.com/watch?v=YhQxtrn0e7E&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Boris Kozinsky – Symmetry and Uncertainty-aware Models of Interatomic Interactions for Fast Molecular Dynamics
https://www.youtube.com/watch?v=Pa0DWEd6qQc&ab_channel=ICTPCondensedMatterandStatisticalPhysics

David Peter Kovacs – Atomic Cluster Expansion based Force Fields for Molecular Materials
https://www.youtube.com/watch?v=RDsT4HFkr-Y&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Ilyes Batatia – A Unified Understanding of Equivariant Interatomic Potentials
https://www.youtube.com/watch?v=nbzoeR4ejPI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Robin Winter – Unsupervised Learning of Group Invariant and Equivariant Representations
https://www.youtube.com/watch?v=fp5qLP5OrS8&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Tuan Le – Unsupervised Representation Learning on Molecular Conformations
https://www.youtube.com/watch?v=b67ee0eRH_A&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Yasemin Bozkurt Varolgüneş – Interpretable Embeddings from Molecular Simulations using Gaussian Mixture Variational Autoencoders
https://www.youtube.com/watch?v=ROioje_I9Dc&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Saso Dzeroski – Learning Explainable Models from Complex Data with Applications in QSAR Modelling
https://www.youtube.com/watch?v=7mWsL0qjiIA&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Francesca Grisoni – Chemical Language Models for de Novo Molecule Design
https://www.youtube.com/watch?v=SuDHlDlB6yU&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Sebastiano Saccani – Industrial Applications of Generative Machine Learning Methods
https://www.youtube.com/watch?v=g0DVQEoUbZ8&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Alessandro Laio, Francesca Grisoni, Kristof Schütt, Saso Dzeroski, Andrea Anelli, Julia Westermayr, moderated by Kevin Rossi – Panel Discussion 1
https://www.youtube.com/watch?v=dPGrRJ_uiwI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Jigasa Nigam – Towards Message Passing with Equivariant N-centered Representations
https://www.youtube.com/watch?v=OfC0vUqw6FA&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Julia Westermayr – Deep Learning for Excited States and Molecular Design
https://www.youtube.com/watch?v=ta0lUMsIjPk&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Lars Banko – Data-driven High-throughput Experimentation Using Combinatorial Material Science Methods and ML
https://www.youtube.com/watch?v=mE2NvFZZfXg&ab_channel=ICTPCondensedMatterandStatisticalPhysics

I-Ju Chen – Precise Atom Manipulation Through Deep Reinforcement Learning
https://www.youtube.com/watch?v=ZaHI0vLHjGY&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Sintjia Stevanoska – Relating the Composition and Mechanical Properties of Tungsten-based Composited by Using Machine Learning
https://www.youtube.com/watch?v=PG3h9EToC4I&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Nataliya Lopanitsyna – Alchemical Machine Learning for High Entropy Alloys
https://www.youtube.com/watch?v=m3g9jWc3WfY&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Zhi Li – The Phase Diagram of Iron up to Earth’s Inner Core Conditions
https://www.youtube.com/watch?v=AMC1vWOl5tw&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Núria López – Machine Learning Techniques in Heterogeneous Catalysis
https://www.youtube.com/watch?v=Khul4neSbYA&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Johannes Margraf – Predicting Molecular Properties through Machine Learned Energy Functionals
https://www.youtube.com/watch?v=EiDF8X8YzZI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Zachary Ulissi – Continued progress towards generalizable machine learning models in computational catalysis
TBA

Jarno Laakso – Compositional Engineering of Perovskites for Solar Energy Applications with Machine Learning
https://www.youtube.com/watch?v=tngrMqLSQtI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Jonathan Schmidt – Machine Learning Thermodynamic Stability of Materials
https://www.youtube.com/watch?v=8_OSghDgHP8&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Felix Arendt – Evaluation of descriptors for property predictions of glasses by machine learning
https://www.youtube.com/watch?v=JqeM1XHxgvI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Boris Kozinsky, Zachary Ulissi, Núria López, Rianne Van Der Berg, Lars Banko, moderated by Patrick Rinke – Panel Discussion 2
https://www.youtube.com/watch?v=dPGrRJ_uiwI&ab_channel=ICTPCondensedMatterandStatisticalPhysics

Claudio Zeni, Kevin Rossi with Matteo Carli and I-Ju Chen – Closing Remarks, Best Poster and Best Contributed Talk Prizes
https://www.youtube.com/watch?v=Kwu2Fo0l_4o&ab_channel=ICTPCondensedMatterandStatisticalPhysics