Eric Nalisnick

Assistant Professor@Johns Hopkins University·美国·OpenReview

研究方向

Human-AI collaboration and teaming · Human-in-the-Loop Learning · Uncertainty quantification · Variational Inference · Probabilistic Modeling · Out-of-Distribution Detection · Deep Learning · Bayesian Methods

4.0

Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence

ICLR 2025Poster

三作

4.5

Temporal Test-Time Adaptation with State-Space Models

合作者 (20)

Christian A. Naesseth

Eric Nalisnick

Safe and Efficient In-Context Learning via Risk Control

Monitoring Risks in Test-Time Adaptation

ELBOing Stein: Variational Bayes with Stein Mixture Inference

Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence

Temporal Test-Time Adaptation with State-Space Models