3 papers
physics.comp-ph2026
Reconstructing local environments from concise atomistic representations
Jigyasa Nigam, Tuong Phung, Ameya Daigavane +2
Symmetry-based representations of local atomic structure, such as the power spectrum or bispectrum, are routinely used to characterize the structural diversity of datasets and as i…
cs.LG2026
Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics
YuQing Xie, Ameya Daigavane, Mit Kotak +1
-equivariant neural networks have proven to be effective in a wide range of 3D modeling tasks. A fundamental operation of such networks is the tensor product, which allows in…
cs.LG2025
Matching the Optimal Denoiser in Point Cloud Diffusion with (Improved) Rotational Alignment
Ameya Daigavane, YuQing Xie, Bodhi P. Vani +3
Diffusion models are a popular class of generative models trained to reverse a noising process starting from a target data distribution. Training a diffusion model consists of lear…