Neural Information Processing Systems http://nips.cc/

Inference via knowledge compilation has also been used for many applications in neuro-symbolic AI,suchasconstrained generation [2,54]andneural logic programming [34,28].

We perform experiments on high-dimensional Gaussians, Lotka-V olterra dynamics, and a Pickover attractor.

Bayesian deep learning has always garnered substantial interest in the machine learning community.

Our results are corroborated with experiments.

We introduce a novel score-based diffusion framework named Twigs that incorporates multiple co-evolving flows for enriching conditional generation tasks. Specifically, a central or trunk diffusion process is associated with a primary variable (e.g., graph structure), and additional offshoot or stem processes are dedicated

Symmetries have proven useful in machine learning models, improving generalisation and overall performance.