AISTATS 2023: Meta-Uncertainty in Bayesian Model Comparison

(14:59)

AISTATS 2023: PF2ES for Multi-Objective Bayesian Optimization

(12:31)

AISTATS 2023 - Learning Treatment Effects from Observational and Experimental Data

(11:38)

Robust and Agnostic Learning of Conditional Distributional Treatment Effects (AISTATS 2023)

(16:33)

AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

(12:9)

AISTATS 2023

(15:)

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals (AISTATS 2023)

(15:4)

Distill n' Explain: explaining graph neural networks using simple surrogates [AISTATS 2023]

(19:29)

AISTATS 2023 Keynote - Tamara Broderick - Can Dropping a Little Data Change Conclusions?

(55:40)

Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach (AISTATS 2023)

(12:46)

AISTATS 2023 - Complex-to-Real Sketches for Tensor Products

(15:3)

Temporal Graph Neural Networks for Irregular Data, AISTATS 2023 Presentation

(9:30)

AISTATS 2023 Talk - TabLLM: Few-shot Classification of Tabular Data with Large Language Models

(14:56)

AISTATS Presentation

(9:45)

[AISTATS 2023] Don't be fooled: label leakage in explanation methods...

(9:27)

AISTATS paper reaction | Mega Compilation!!

(3:31)

PCP AISTATS 2023

(10:29)

The Lie-Group Bayesian Learning Rule (AISTATS 2023)

(14:42)