FWIW the license they chose (CC-BY-NC) isn't actually open source. But at least the code is there if you want to run it.
Aaron Meurer On Thu, Apr 16, 2020 at 3:50 AM S.Y. Lee <[email protected]> wrote: > > They have opened the source code and the dataset > https://github.com/facebookresearch/SymbolicMathematics > > On Saturday, January 11, 2020 at 2:25:40 AM UTC+9, Aaron Meurer wrote: >> >> For those who didn't see, the final paper was posted with many updates >> https://arxiv.org/abs/1912.01412. The newest version addresses some of >> the things that were discussed here, and makes more use of SymPy, >> including demonstrating some integrals that SymPy cannot solve, as >> well as making it clearer how SymPy was used to check the results of >> integration. >> >> Aaron Meurer >> >> On Tue, Oct 8, 2019 at 8:16 PM oldk1331 <[email protected]> wrote: >> > >> > (This mail is copied from my response at maxima mailing list.) >> > >> > My opinion on this paper: >> > >> > First, their dataset (section 4.1) can be greatly improved using >> > existing integration theory, Risch algorithm says that every elementary >> > function integration can be reduced to 3 cases: transcendental (only >> > contains rational functions and exp/log/tan, other trigonometric >> > functions can transform to 'tan'), algebraic (only contains rational >> > functions and nth-root ^), and mixed-case. >> > >> > So their method to prepare the dataset concentrates greatly on the >> > transcendental cases, extremely lacks algebraic cases. And they uses >> > only numbers from -5 to 5. I think it scales badly for wider ranges of >> > numbers. >> > >> > For transcendental cases, I think FriCAS has fully implemented this >> > branch of Risch algorithm, so it should always give correct result. For >> > algebraic cases, I highly doubt that this ML program can solve >> > integrate(x/sqrt(x^4 + 10*x^2 - 96*x - 71), x) = >> > log((x^6+15*x^4+(-80)*x^3+27*x^2+(-528)*x+781)*(x^4+10*x^2+(-96)*x+(-71))^(1/2)+(x^8+20*x^6+(-128)*x^5+54*x^4+(-1408)*x^3+3124*x^2+10001))/8 >> > >> > In fact, I doubt that this program can solve some rational function >> > integration that requires Lazard-Rioboo-Trager algorithm to get >> > simplified result. >> > >> > So I think this ML program has many flaws, but we can't inspect it. >> > >> > > I'm also curious (and sceptical) on just how well a neural network can >> > > "learn" symbolic mathematics and specifically an integration >> > > algorithm. Another interesting thing to do would be to try to train a >> > > network to integrate rational functions, to see if it can effectively >> > > recreate the algorithm (for those who don't know, there is a complete >> > > algorithm which can integrate any rational function). My guess is that >> > > this sort of thing is still beyond the capabilities of a neural >> > > network. >> > >> > I totally agree. >> > >> > - Qian >> > >> > -- >> > You received this message because you are subscribed to the Google Groups >> > "sympy" group. >> > To unsubscribe from this group and stop receiving emails from it, send an >> > email to [email protected]. >> > To view this discussion on the web visit >> > https://groups.google.com/d/msgid/sympy/ca99c7a0-b372-82cb-74e6-2ff978f40d54%40gmail.com. > > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/9d091321-07dd-4ade-9442-795282269627%40googlegroups.com. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CAKgW%3D6J2RkAM2zQrcSLfEH0X6D%3DH0-Jt1tTmwXQHz7aOO%2B4yDg%40mail.gmail.com.
