Building Knowledge That’s Truly Implementable Tomorrow

NeurIPS 2019 Workshop on Bayesian Deep Learning

Deep Gaussian processes for weakly supervised learning: tumor mutation burden (TMB) prediction

Sunho Park, Hongming Xu, Tae Hyun Hwang, Saehoon Kim

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NeurIPS 2019 Workshop on Sets & Partitions

Towards deep amortized clustering

Juho Lee, Yoonho Lee and Yee Whye Teh

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NeurIPS 2019 Workshop on Graph Representation Learning

Graph Embedding VAE: A Permutation Invariant Model of Graph Structure

Tony Duan and Juho Lee

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Critical Care

A Deep Learning Model for Real-time Mortality Prediction in Critically ill Children

* Soo Yeon Kim, * Saehoon Kim, Joongbum Cho, Young Suh Kim, In Suk Sol, Youngchul Sung, Inhyeok Cho, Minseop Park, Haerin Jang, Yoon Hee Kim, ** Kyung Won Kim and Myung Hyun Sohn (*: equal contribution, **: corresponding)

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ACL 2019

Episodic Memory Reader: Learning What to Remember for Question Answering from Streaming Data

Moonsu Han, Minki Kang, Hyunwoo Jung, Sung Ju Hwang

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ICML 2019

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks

Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh

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ICML 2019 (full oral presentation)

Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior

* Fadhel Ayed, * Juho Lee, François Caron (* indicates equal contribution)

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ICML 2019 (full oral presentation)

Trimming the ℓ 1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning

Jihun Yun, Peng Zheng, Aurelie Lozano, Aleksandr Aravkin, Eunho Yang

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ICML 2019

Learning What and Where to Transfer

Yunhun Jang, Hankook Lee, Sung Ju Hwang, Jinwoo Shin

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ICML 2019

Spectral Approximate Inference

Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin

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