9 citations · 15 across the 5 of their papers we have counts for
5 papers
Deep Stochastic Processes via Functional Markov Transition Operators
Jin Xu, Emilien Dupont, Kaspar Märtens +2
We introduce Markov Neural Processes (MNPs), a new class of Stochastic Processes (SPs) which are constructed by stacking sequences of neural parameterised Markov transition operato…
DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding
Jianhao Yan, Jin Xu, Fandong Meng +2
Minimum Bayesian Risk Decoding (MBR) emerges as a promising decoding algorithm in Neural Machine Translation. However, MBR performs poorly with label smoothing, which is surprising…
Group Equivariant Subsampling
Jin Xu, Hyunjik Kim, Tom Rainforth +1
Subsampling is used in convolutional neural networks (CNNs) in the form of pooling or strided convolutions, to reduce the spatial dimensions of feature maps and to allow the recept…
MetaFun: Meta-Learning with Iterative Functional Updates
Jin Xu, Jean-Francois Ton, Hyunjik Kim +2
We develop a functional encoder-decoder approach to supervised meta-learning, where labeled data is encoded into an infinite-dimensional functional representation rather than a fin…
Controllable Semantic Image Inpainting
Jin Xu, Yee Whye Teh
We develop a method for user-controllable semantic image inpainting: Given an arbitrary set of observed pixels, the unobserved pixels can be imputed in a user-controllable range of…