← All tracks

JAX Numerical Computing

Linear algebra, decompositions, FFT, convolutions, sparse arrays, polynomial fitting, numerical stability. Scientific computing in JAX.

0 / 25 solved Continue →
  1. 1. ○ linalg.solve
  2. 2. ○ linalg.inv
  3. 3. ○ slogdet for Stable log|det|
  4. 4. ○ linalg.norm (Frobenius)
  5. 5. ○ linalg.matrix_power
  6. 6. ○ Cholesky Decomposition
  7. 7. ○ QR Decomposition
  8. 8. ○ SVD Singular Values
  9. 9. ○ eigh: Symmetric Eigendecomp
  10. 10. ○ 1-D FFT Magnitude
  11. 11. ○ Real FFT (rfft)
  12. 12. ○ 2-D FFT DC Component
  13. 13. ○ 1-D Conv via lax.conv_general_dilated
  14. 14. ○ 2-D Conv via lax.conv_general_dilated
  15. 15. ○ Conv Padding & Strides
  16. 16. ○ BCOO from Dense
  17. 17. ○ Sparse Matrix-Vector Product
  18. 18. ○ BCOO Round-Trip
  19. 19. ○ Polynomial Fitting via polyfit
  20. 20. ○ Polynomial Evaluation via polyval
  21. 21. ○ Linear Interpolation
  22. 22. ○ Numerically Stable logsumexp
  23. 23. ○ Stable log_softmax
  24. 24. ○ log1p / expm1 for Small Values
  25. 25. ○ Cumulative Trapezoidal Integration