Abstract: Federated learning has emerged as a key paradigm for distributed optimization under privacy and communication constraints, yet classical aggregation schemes such as Federated Averaging ...
The forward and inverse kinematics networks of the data-driven path share a residual MLP backbone: MLP architecture for kinematics approximations. Inputs are projected into a 128-dim latent space and ...
Efficiently steering generative models toward pharmacologically relevant regions of chemical space is a major challenge in drug discovery under low-data regimes. We present VECTOR+ ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results