Researcher, Google
2 papers at NeurIPS 2025
We propose SmoothDiff, a novel feature attribution method leveraging automatic differentiation, directly targeting nonlinearities responsible for the shattered gradient problem.
This papers introduces a Diffusion Transformer (DiT) for sampling 3D molecular conformers.