JOSS Papers: Automatic Differentiation

All Papers
3996
 Published Papers
3516
 Active Papers
479
published Published about 2 months ago

FluxOptics.jl: A Differentiable Wave Optics Framework for Inverse Design in Julia

Julia Python
@anscoil
10.21105/joss.09734
published Published 3 months ago

FDTDX: High-Performance Open-Source FDTD Simulation with Automatic Differentiation

Python
@ymahlau
10.21105/joss.08912
published Published 9 months ago

Tesseract Core: Universal, autodiff-native software components for Simulation Intelligence

Python
@boltzmannbrain
10.21105/joss.08385
published Published 11 months ago

PathSim - A System Simulation Framework

Python
@milanofthe
10.21105/joss.08158
published Published about 1 year ago

AutoPDEx: An Automized Partial Differential Equation solver based on JAX

Python
@BodeTobias
10.21105/joss.07300
published Published almost 2 years ago

Catalyst: a Python JIT compiler for auto-differentiable hybrid quantum programs

Python
@josh146
10.21105/joss.06720
published Published over 2 years ago

BridgeStan: Efficient in-memory access to the methods of a Stan model

R C Julia
@roualdes
10.21105/joss.05236
published Published almost 3 years ago

QAOA.jl: Toolkit for the Quantum and Mean-Field Approximate Optimization Algorithms

Julia
@timbode
10.21105/joss.05364
published Published about 3 years ago

SICOPOLIS-AD v2: tangent linear and adjoint modeling framework for ice sheet modeling enabled by automatic differentiation tool Tapenade

C Fortran Python
@Shreyas911
10.21105/joss.04679
published Published over 4 years ago

torchquad: Numerical Integration in Arbitrary Dimensions with PyTorch

Python
@gomezzz
10.21105/joss.03439
Displaying papers 1 - 10 of 13 in total

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ISSN 2475-9066