Researchers explore AI's role in scientific modeling, from historical breakthroughs to modern Bayesian frameworks like ModelSMC.

Anthropic published a guest research essay on November 6, 2026, in which AI for Science grantees Jakob Macke, Daniel Gedon ...

We will take a deep dive into reliable AI-related papers published on arXiv around the last day (around October 21, 2026), ...

Bayesian inference offers a principled mechanism for updating beliefs by combining prior distributions with observed data via Bayes’s theorem. Central to this approach is the specification of a ...

Researchers have developed an importance-sampling-based black box variational inference algorithm that reuses earlier ...

Inverse problems arise when one seeks to recover unknown parameters or functions from indirect, noisy observations via a forward model. The Bayesian framework casts this recovery as the updating of a ...

Are Induction and Deduction Not Enough?Hybrid AI (Neuro-Symbolic AI), which combines the flexibility of neural networks with the rigor of symbolic logic, is attracting attention.The idea is to combine ...