SYNTENSOR

We're hiring! Syntensor is combining methods in geometric deep learning with stochastic neural graph differential equations to model dynamic biological systems at scale. We believe their work is the most advanced commercial application of Torchdyn at scale... Torchdyn is maintained by DiffeqML, an open research group for the intersection of deep learning and dynamical systems... Torchdyn leverages modern PyTorch best practices and handles training with pytorch-lightning. We build Graph Neural ODEs utilizing the Graph Neural Networks (GNNs) API of dgl. For a complete list of references, check pyproject.toml. We offer a suite of ODE solvers, sensitivity methods, root finding algorithms and other common utilities for numerical deep learning.

Also known as: Syntensor Inc, torchdyn