Physics
Multi fidelity models
Data-driven multi-scale sampling, multi-resolution, super-resolution
2020-08-24
– 2023-11-20Machine learning for partial differential equations
2017-05-15
– 2023-11-17Feedback system identification, not necessarily linear
Learning dynamics from data
2016-08-01
– 2023-11-15Hydrology, applied
Rivers, aquifers and other wet things that can flood your house
2020-09-07
– 2023-10-27Physics-informed neural networks
2019-10-15
– 2023-10-19Neural PDE operator learning
Especially forward operators. Image-to-image regression, where the images encode a physical process.
2019-10-15
– 2023-10-19Decoupling the economy from energy
2021-05-21
– 2023-10-03Material basis of the economy
2011-10-17
– 2023-10-03Power generation, engineering and use
On the magical, terrible requisites of keeping the lights on
2021-05-04
– 2023-09-25Probabilistic numerics
2023-07-13
– 2023-09-25Machine learning for climate systems
2020-04-02
– 2023-09-25Materials informatics
Machine learning in condensed matter physics, chemistry and materials science
2023-08-01
– 2023-08-08Learnable coarse-graining
Approximate meso-scale physics
2020-08-24
– 2023-08-01Statistical mechanics of statistics
2016-12-01
– 2023-06-02Neural learning dynamical systems
2018-08-13
– 2023-05-23Differentiable PDE solvers
2017-05-15
– 2023-05-15Model order reduction
2015-03-22
– 2023-04-21ΦFlow
A modern python computational fluid dynamics library for ML research
2022-06-24
– 2023-04-17Symbolic regression
2023-03-14Machine learning for physical sciences
Turbulent mixing at the boundary between disciplines with differing inertia and viscosity
2017-05-15
– 2022-12-07Hamiltonian and Langevin Monte Carlo
Physics might be on to something
2018-07-31
– 2022-11-14Deep learning as a dynamical system
2018-08-13
– 2022-10-30The edge of chaos
Computation, evolution, competition and other past-times of faculty
2016-12-01
– 2022-10-30Physical infrastructure
2022-09-24Hydrology, applied
Rivers, aquifers and other wet things that can flood your house
2020-09-07
– 2022-06-30Emergent spacetime
What are qubits again?
2022-05-26Measure-valued stochastic processes
Moving masses
2020-10-16
– 2022-05-03Partition-valued random variates
2022-04-01Measure-valued random variates
Including completely random measures and many generalizations
2020-10-16
– 2022-03-30Learning Gaussian processes which map functions to functions
2020-12-07
– 2022-02-25Learning with conservation laws, invariances and symmetries
2020-04-11
– 2022-02-25Learning on manifolds
Finding the lowest bit of a krazy straw, from the inside
2011-10-21
– 2022-01-26Quantum computing
2017-12-14
– 2022-01-21Feedback system identification, linear
2016-07-27
– 2022-01-21Convolutional subordinator processes
2021-03-08
– 2021-12-01Convolutional stochastic processes
Moving averages of noise
2021-03-01
– 2021-08-16Convolutional Gaussian processes
2021-03-01Stochastic processes on manifolds
2021-03-01Emulators and surrogate models via ML
Shortcuts in scientific simulation using ML
2020-08-12
– 2020-08-26Bushfire models
2020-09-07
– 2020-08-19Sparse stochastic processes identification and sampling
Discrete sample representation of sparse continuous stochastic processes
2018-11-22
– 2018-10-29Quantum information in physics
What are qubits again?
2017-07-24
– 2017-12-14Lagrangian mechanics
2015-02-11
– 2017-06-18Special functions
2014-07-25
– 2016-12-21Dynamical systems
2016-04-26
– 2016-07-27Thermodynamics
2015-02-20
– 2016-01-18Coarse graining
2014-11-11
– 2015-12-02Earthquakes
2015-07-14 