Accurate predictions on small data (and time series) with the tabular foundation model TabPFN

42:54
Chronos: Time series forecasting in the age of pretrained models

48:45
Xingyou (Richard) Song - OmniPred: Towards Universal Regressors with Language Models

17:05
TabPFN: Deep Learning for Tabular Data is Here! (Prof. Frank Hutter explains)

58:18
Andreas Mueller - MotherNet: A Foundational Hypernetwork for Tabular Classification

58:00
Antonio Mezzacapo: Quantum diagonalization methods for lattice models

45:33
Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

35:19
Vanilla Bayesian Optimization Performs Great in High Dimensions

53:02