5 citations · 12 across the 19 of their papers we have counts for
6 papers · 1 filter
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Balhae Kim, Hyungi Lee, Juho Lee
A Bayesian pseudocoreset is a compact synthetic dataset summarizing essential information of a large-scale dataset and thus can be used as a proxy dataset for scalable Bayesian inf…
Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary
Sojung Lucia Kim, Taehong Jang, Joonmo Ahn +2
A named entity recognition and classification plays the first and foremost important role in capturing semantics in data and anchoring in translation as well as downstream study fo…
Traversing Between Modes in Function Space for Fast Ensembling
EungGu Yun, Hyungi Lee, Giung Nam +1
Deep ensemble is a simple yet powerful way to improve the performance of deep neural networks. Under this motivation, recent works on mode connectivity have shown that parameters o…
Regularizing Towards Soft Equivariance Under Mixed Symmetries
Hyunsu Kim, Hyungi Lee, Hongseok Yang +1
Datasets often have their intrinsic symmetries, and particular deep-learning models called equivariant or invariant models have been developed to exploit these symmetries. However,…
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
Moonseok Choi, Hyungi Lee, Giung Nam +1
Given the ever-increasing size of modern neural networks, the significance of sparse architectures has surged due to their accelerated inference speeds and minimal memory demands.…
Martingale Posterior Neural Processes
Hyungi Lee, Eunggu Yun, Giung Nam +2
A Neural Process (NP) estimates a stochastic process implicitly defined with neural networks given a stream of data, rather than pre-specifying priors already known, such as Gaussi…