Aniruddh Raghu | DeepAI

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∙ 07/20/2023

Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series

Self-supervised learning (SSL) for clinical time series data has receive...

0 Aniruddh Raghu, et al. ∙

∙ 04/09/2022

Data Augmentation for Electrocardiograms

Neural network models have demonstrated impressive performance in predic...

11 Aniruddh Raghu, et al. ∙

∙ 11/02/2021

Meta-Learning to Improve Pre-Training

Pre-training (PT) followed by fine-tuning (FT) is an effective method fo...

14 Aniruddh Raghu, et al. ∙

∙ 03/04/2021

Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction

The impact of machine learning models on healthcare will depend on the d...

27 Aniruddh Raghu, et al. ∙

∙ 11/05/2020

Teaching with Commentaries

Effective training of deep neural networks can be challenging, and there...

3 Aniruddh Raghu, et al. ∙

∙ 09/19/2019

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

An important research direction in machine learning has centered around ...

5 Aniruddh Raghu, et al. ∙

∙ 11/23/2018

Model-Based Reinforcement Learning for Sepsis Treatment

Sepsis is a dangerous condition that is a leading cause of patient morta...

0 Aniruddh Raghu, et al. ∙

∙ 07/03/2018

Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters

In this work, we consider the problem of estimating a behaviour policy f...

0 Aniruddh Raghu, et al. ∙

∙ 05/23/2018

Representation Balancing MDPs for Off-Policy Policy Evaluation

We study the problem of off-policy policy evaluation (OPPE) in RL. In co...

0 Yao Liu, et al. ∙

∙ 11/27/2017

Deep Reinforcement Learning for Sepsis Treatment

Sepsis is a leading cause of mortality in intensive care units and costs...

0 Aniruddh Raghu, et al. ∙

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