Adam Hartshorne

Results 24 issues of Adam Hartshorne

When building the library and various projects, I receive a number of #C2491 errors e.g. error C2491: 'ApproxMVBB::approximateMVBBGridSearch': definition of dllimport function not allowed I believe it is this problem...

The following two bits of code compile ok with MSVC, but using LLVM/Clang produces the following errors. Using the code in print.cpp ``` BOOST_HOF_STATIC_FUNCTION(simple_print) = fix(first_of( BOOST_HOF_LIFT(print_with_cout), BOOST_HOF_LIFT(print_with_range), BOOST_HOF_LIFT(print_with_tuple) ));...

I recently came across this paper from last years NeurIPS https://ghliu.github.io/assets/pdf/neurips-snopt-slides.pdf https://github.com/ghliu/snopt I was wondering if there are any plans to extend Diffrax to support this improvement to the standard...

question

I am sure you are probably aware, but the basic examples like ode_demo and latent_ode are broken in the rewrite branch. The size of the tensor returned from odeint is...

Wilson and Terenin introduced "Efficiently Sampling Functions from Gaussian Process Posteriors" which is now widely used for, as the title states, efficient sampling (and won an honourable mention for best...

enhancement

#I have built the code using VS2015 on Windows 10. I am as instructed using the forked version of Eigen and the latest OpenSubDiv from the dev branch. With this...

As the title states, although the library and the example build successfully with QT 5.9 (x64 Windows 10), upon running it and selecting to add a new pane it causes...

This may be of interest. > Does the use of auto-differentiation yield reasonable updates to deep neural networks that represent neural ODEs? Through mathematical analysis and numerical evidence, we find...

The following Linear Operator Library has recently been released, https://cola.readthedocs.io/en/latest/index.html, which allows for lazy evaluation in the following manner, `lazy_A = cola.fns.lazify(A)` where the type of lazy_A will be a...

question

As a minimal example, lets say we have something like this (the real situation is custom modules which contain other modules, hence the flatten). If I look at flat_model obviously...

question