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 ...

Both humans and other animals are good at learning by inference, using information we do have to figure out things we cannot observe directly. New research from the Center for Mind and Brain at the ...

Adaptive Neuro-Fuzzy Inference Systems (ANFIS) integrate the interpretability of fuzzy logic with the adaptive learning capabilities of neural networks, forming a powerful framework for tackling ...

Paper: "Robust Nonparametric Bias-Corrected Inference in the Regression Discontinuity Design", (joint work with Sebastian Calonico and Rocio Titiunik).

“The rapid release cycle in the AI industry has accelerated to the point where barely a day goes past without a new LLM being announced. But the same cannot be said for the underlying data,” notes ...