5 papers
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
David R. Johnson, Alexander Sietsema, Rishabh Anand +3
We introduce vector diffusion wavelets (VDWs), a novel family of wavelets inspired by the vector diffusion maps algorithm that was introduced to analyze data lying in the tangent b…
Platonic Transformers: A Solid Choice For Equivariance
Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels +7
While widespread, Transformers lack inductive biases for geometric symmetries common in science and computer vision. Existing equivariant methods often sacrifice the efficiency and…
Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
Alex Morehead, Miruna Cretu, Antonia Panescu +14
General-purpose 3D modeling in chemistry encompasses molecules and materials, requiring both generative and predictive capabilities. However, most existing AI approaches are optimi…
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Neil He, Rishabh Anand, Hiren Madhu +5
Large language models (LLMs) have shown great success in text modeling tasks across domains. However, natural language exhibits inherent semantic hierarchies and nuanced geometric…
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design
Rishabh Anand, Chaitanya K. Joshi, Alex Morehead +7
We introduce RNA-FrameFlow, the first generative model for 3D RNA backbone design. We build upon SE(3) flow matching for protein backbone generation and establish protocols for dat…