Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations

no code implementations • 17 May 2022 • Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner, Hartmut Maennel, Sergii Kashubin, Daniel Ahlin, Michael Gastegger, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Klaus-Robert Müller

Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes.

Variance Reduction in Deep Learning: More Momentum is All You Need

no code implementations • 23 Nov 2021 • Lionel Tondji, Sergii Kashubin, Moustapha Cisse

Variance reduction (VR) techniques have contributed significantly to accelerating learning with massive datasets in the smooth and strongly convex setting (Schmidt et al., 2017; Johnson & Zhang, 2013; Roux et al., 2012).

Data Augmentation Distributed Optimization

Continental-Scale Building Detection from High Resolution Satellite Imagery

no code implementations • 26 Jul 2021 • Wojciech Sirko, Sergii Kashubin, Marvin Ritter, Abigail Annkah, Yasser Salah Eddine Bouchareb, Yann Dauphin, Daniel Keysers, Maxim Neumann, Moustapha Cisse, John Quinn

Identifying the locations and footprints of buildings is vital for many practical and scientific purposes.

Instance Segmentation Semantic Segmentation

Measuring Compositional Generalization: A Comprehensive Method on Realistic Data

2 code implementations • ICLR 2020 • Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet

We present a large and realistic natural language question answering dataset that is constructed according to this method, and we use it to analyze the compositional generalization ability of three machine learning architectures.

BIG-bench Machine Learning Question Answering