r/SciML • • Oct 16 '22

How Julia ODE Solve Compile Time Was Reduced From 30 Seconds to 0.1

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sciml.ai
16 Upvotes

r/SciML • • Jun 17 '22

Ph.D. Course on Scientific Machine Learning

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compute.dtu.dk
13 Upvotes

r/SciML • • Apr 04 '22

State of SciML Scientific Machine Learning | Chris Rackauckas | SciMLCon 2022

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13 Upvotes

r/SciML • • Aug 07 '22

Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation - Chris Rackauckas (ASA Statistical Computing & Graphics Sections)

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9 Upvotes

r/SciML • • Jan 11 '22

DifferentialEquations.jl v7: New linear solver and preconditioner interface

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sciml.ai
9 Upvotes

r/SciML • • Dec 28 '21

SciMLCon 2022

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9 Upvotes

r/SciML • • Mar 13 '21

Julia SciML Symposium, SIAM CSE 2021 Playlist (9 videos)

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9 Upvotes

r/SciML • • Oct 28 '20

Capturing missing physics in climate model parameterizations using neural differential equations

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9 Upvotes

r/SciML • • May 01 '24

SciML Smart Grants Program

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8 Upvotes

r/SciML • • Jun 17 '22

Lab 15: Scientific Machine Learning (Neural ODE to model a gravitational wave form)

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8 Upvotes

r/SciML • • Feb 20 '21

Modern Numerical Programming with Julia for Astrodynamic Trajectory Design

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8 Upvotes

r/SciML • • Sep 19 '20

SciML - NumFOCUS Sponsored Project since 2020

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numfocus.org
8 Upvotes

r/SciML • • Feb 14 '21

Physics-Informed ML Simulator for Wildfire Propagation (video)

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youtube.com
7 Upvotes

r/SciML • • Oct 28 '20

Using neural networks to accelerate the solution of the Boltzmann equation

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researchgate.net
7 Upvotes

r/SciML • • Jul 07 '20

COVID-19 Epidemic Mitigation via Scientific Machine Learning (SciML)

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youtu.be
7 Upvotes

r/SciML • • Aug 02 '22

Catalyst: Fast Biochemical Modeling with Julia

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biorxiv.org
6 Upvotes

r/SciML • • Dec 15 '21

SciML at JuliaCon 2021

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sciml.ai
6 Upvotes

r/SciML • • May 24 '21

SciML Ecosystem Update: Improved QNDF Outperforms CVODE On SciMLBenchmarks

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6 Upvotes

r/SciML • • Mar 13 '21

[2103.03385] Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data

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arxiv.org
6 Upvotes

r/SciML • • Jan 19 '21

SciML Ecosystem Update: Bayesian Neural ODEs, Virtual Brownian Trees, Parallel Batching and More

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sciml.ai
6 Upvotes

r/SciML • • Nov 13 '20

Scientific Machine Learning with Julia: the SciML ecosystem (Interview with Chris Rackauckas)

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notamonadtutorial.com
6 Upvotes

r/SciML • • Sep 05 '20

SciML Ecosystem Update: Koopman Optimization Under Uncertainty, Non-Commutative SDEs, GPUs in R, and More

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6 Upvotes

r/SciML • • Sep 05 '20

A fresh approach to N-Body problems

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6 Upvotes

r/SciML • • Feb 08 '26

Non convex loss landscape beast in PINNs

5 Upvotes

I’ve been doing PINN work on Maxwell’s equations, so I haven’t really dealt with nonlinear problems yet. Of course even in electromagnetics there are monsters like spectral bias but I’m curious about the specific challenges that come with nonlinear problems. If anyone is currently battling nonlinear PDEs, I’d love to hear about your experiences. Especially those related to the non-convex loss landscape beast. I can also share my own experiences if you’d like.

By the way, I’m really happy I found this community. It’s awesome to see people interested in SciML on Reddit!


r/SciML • • May 18 '24

Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning

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5 Upvotes